JP2018075754A - Data output regulation device for molding three-dimensional object - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a data output regulation device for molding a three-dimensional object capable of more suitably determining the appropriateness of output of a 3D polygon model.SOLUTION: There is provided a data output regulation device for molding a three-dimensional object comprising: a regulation model data base 60 registered with an area ratio distribution as a frequency distribution based on a value obtained by dividing the area of the circumcircle of a triangle formed by the prescribed points of three polygons in a regulation model by the square root of the area of the triangle; frequency distribution calculation means 10 calculating an area ratio distribution as a frequency distribution based on a value obtained by dividing the area of the circumcircle of a triangle formed by the prescribed points of three polygons in an object model by the square root of the area of the triangle; and frequency distribution collation means 40 of collating the area ratio distribution of the object model with the area ratio distribution of the regulation model and deciding where output should be regulated or not.SELECTED DRAWING: Figure 4

Description

  In the present invention, when using a three-dimensional object forming apparatus such as a 3D printer that processes a resin or the like to form a three-dimensional object based on data representing the three-dimensional object, it is determined which is inappropriate for output from the three-dimensional object forming apparatus. It relates to technology.

  In recent years, 3D printers that process and model resin, gypsum, and the like based on data representing a three-dimensional object have become widespread as three-dimensional object modeling apparatuses. The 3D printer outputs a three-dimensional object using a polygon model that represents a three-dimensional shape of the three-dimensional object as a set of polygons. As a medical application of 3D printer, 3D printer output modeling data (polygon model) is created based on CT / MRI image (DICOM format 3D voxel data) taken by medical diagnosis. Attempts have been made to output organ models for informed consent or to create artificial organs (blood vessels, bones, joints, etc.) for implantation in the body.

  3D printers have an innovation that can propagate not only information but also things remotely to the remote location via the Internet. For this reason, there has been a problem that dangerous materials such as guns and swords that have been regulated by customs have been distributed across the border in the form of data and can be easily obtained as 3D printers. In order to cope with this, the applicant has developed a technique for determining whether or not to restrict the output when outputting a three-dimensional object from a 3D printer based on a 3D polygon model (Patent Literature). 1 and 2).

JP, 2006-107471, A JP, 2006-124241, A

  In the techniques described in Patent Documents 1 and 2, distance distribution and angle distribution are created from the relationship between predetermined polygons for each of the target model that is the polygon model to be output and the restriction model that is the polygon model to be restricted, and collation is performed. By doing so, it is determined whether or not the output of the target model should be regulated.

  However, even when collation is performed using the techniques described in Patent Documents 1 and 2, there may be a situation in which what should be regulated is output or what may be output cannot be output. there were.

  Therefore, an object of the present invention is to provide a three-dimensional object formation data output restriction device that can more appropriately determine whether or not the output of a 3D polygon model is appropriate.

In order to solve the above problems, in the first aspect of the present invention,
A device for determining whether or not to regulate when outputting a polygon model expressed as a set of polygons to a three-dimensional object modeling apparatus as three-dimensional object modeling data,
Area that is a frequency distribution based on a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in a restriction model that is a polygon model whose output is to be restricted, by the square root of the area of the triangle A database in which the ratio distribution is registered;
Based on a target model which is a polygon model to be output, a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the target model by the square root of the area of the triangle A frequency distribution calculating means for calculating an area ratio distribution which is a frequency distribution;
A frequency distribution matching unit that collates the area ratio distribution of the target model with the area ratio distribution of the regulation model and determines whether or not the output should be regulated;
There is provided a three-dimensional object shaping data output regulation device characterized by comprising:

  According to the first aspect of the present invention, the frequency distribution is based on a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the restriction model by the square root of the area of the triangle. A database in which the area ratio distribution is registered is provided, and for the target model, the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the target model is divided by the square root of the area of the triangle Since the area ratio distribution, which is a frequency distribution based on the value, is calculated, the area ratio distribution of the target model is compared with the area ratio distribution of the restriction model, and it is determined whether the output should be restricted. It is possible to more appropriately determine the suitability of the output of the 3D polygon model by the area ratio distribution that accurately represents the shape between the polygons by the circumscribed circle.

  In the second aspect of the present invention, the frequency distribution calculating means prepares a one-dimensional array composed of a predetermined number of elements when calculating the area ratio distribution, and calculates the radius of the calculated circumscribed circle. The range of the square of the maximum value of E is evenly divided into the predetermined number, and each area ratio is assigned to one of the predetermined elements based on the value of the area ratio, and the number corresponding to the element To calculate the area ratio distribution.

  According to the second aspect of the present invention, in calculating the area ratio distribution, a one-dimensional array composed of a predetermined number of elements is prepared, and the range of the square of the maximum value of the calculated radius of the circumscribed circle is prepared. Are equally divided into the predetermined number, and each area ratio is assigned to one of the predetermined number of elements based on the value of the area ratio, and the area ratio distribution is calculated based on the number corresponding to the element. Thus, it is possible to calculate an area ratio distribution that reflects sharply the difference in the shape of the triangle.

  Further, in the third aspect of the present invention, the frequency distribution calculating means obtains polygons in the target model in units of three for the target model, and randomly selects the first group, the second group, the third group. The three polygons are selected by classifying them into three groups and selecting one polygon from each group.

  According to the third aspect of the present invention, polygons in the target model are acquired in units of three and randomly classified into three groups of the first group, the second group, and the third group, one from each group. Since polygons are selected, a combination of three polygons for forming a triangle can be created without overlapping each other, and efficient processing can be performed. In particular, grouping can be performed in a state free from peculiar defects by acquiring three units and randomly classifying them into three groups.

  Further, in the fourth aspect of the present invention, the frequency distribution calculating means, when the number of polygons in each group is N / 3, is a random number array in which N / 3 consecutive integers are randomly replaced (shuffled). And generating an inverted random number array in which the order of the random number array from the beginning to the end is reversed, and among the three groups, the random number array is included in one group, and the inverted random number array is included in the other group. The polygons are selected in order from the top of each group after the order of the polygons in the group is changed by applying each array.

  According to the fourth aspect of the present invention, an inverted random number array in which a random number array in which consecutive integers of the number of polygons N / 3 in each group are randomly replaced is created and the order from the beginning to the end of the random number array is reversed After applying the random number array to one group and the inverted random number array to the other group, and changing the order of the polygons in the group, the polygons in order from the top of each group Since the selection order of the polygons of the three groups can be set at random from the position in the three-dimensional space, based on triangles calculated by a combination of random and non-overlapping polygons, An area ratio distribution can be obtained.

In the fifth aspect of the present invention, the frequency distribution calculating means includes
The random number array is applied to the first group of polygons and the inverted random number array is applied to the second group of polygons to change the order, and the polygons are selected without changing the order of the third group of polygons. N / 3 triangles are formed,
The random number array is applied to the second group of polygons and the inverted random number array is applied to the third group of polygons to change the order, and the polygons are selected without changing the order of the first group of polygons. N / 3 triangles are formed,
The random number array is applied to the third group of polygons and the inverted random number array is applied to the first group of polygons to change the order, and the polygons are selected without changing the order of the second group of polygons. N / 3 triangles are formed.

  According to the fifth aspect of the present invention, the random number array is applied to the first group of polygons and the reverse random number array is applied to the second group of polygons to change the order of the polygons without changing the order of the third group of polygons. Select to form N / 3 triangles, apply a random number array to the second group of polygons, and apply an inverted random number array to the third group of polygons to change the order, and change the order of the first group of polygons The polygons are selected to form N / 3 triangles, the order is changed by applying a random number array to the third group of polygons and an inverted random number array to the first group of polygons, and the second group of polygons. Since polygons are selected without changing the order of N / 3 triangles, the number of totas equal to the number N of polygons in the polygon model is set. N pieces of triangular can be formed without overlapping random and each other.

In the sixth aspect of the present invention,
The frequency distribution calculating means includes:
Each time the area ratio distribution is calculated, the calculation of the area ratio distribution is repeated a predetermined number of times by changing the order of polygons in two of the three groups. The average value of the area ratio distribution is the area ratio distribution to be verified.
The frequency distribution calculating means includes:
Each time the frequency distribution is calculated, the order of polygons in two groups out of the three groups is changed, and the frequency distribution is recalculated a predetermined number of times, and the calculated frequency is calculated. The average value of the distribution is a frequency distribution to be verified.

  According to the sixth aspect of the present invention, each time the area ratio distribution is calculated, the process of calculating the area ratio distribution again by changing the order of the polygons in two of the three groups is performed in a predetermined manner. Since the average value of the calculated area ratio distribution is set as the area ratio distribution to be collated, the number of repetitions is repeated a number of times. Therefore, based on the new N triangles that do not overlap with the already calculated N triangles. Since the area ratio distribution is calculated and the area ratio distribution is updated, the area ratio distribution is accurately adjusted so that the area ratio distribution is not biased to a peculiar form because there are too few triangle samples that are combinations of three polygons. A distribution can be obtained.

In the seventh aspect of the present invention,
The frequency distribution calculating means includes:
Each time the area ratio distribution is calculated, the order of polygons in two groups of the three groups is changed, and the process of calculating the area ratio distribution is repeated.
When the area ratio distribution immediately after the calculation is compared with the area ratio distribution obtained immediately before the comparison, and the similarity is recognized as a result of the comparison, the area ratio distribution immediately after the calculation is referred to as the area ratio distribution to be verified. It is a thing to do.

  According to the seventh aspect of the present invention, each time the area ratio distribution is calculated, the process of calculating the area ratio distribution again is performed by changing the order of the polygons in two of the three groups. Compare the area ratio distribution immediately after calculation with the area ratio distribution obtained immediately before that, and if the comparison shows similarities, the area ratio distribution immediately after calculation is the area ratio distribution to be verified. As a result, it is possible to obtain the optimal area ratio distribution while automatically judging whether the area ratio distribution is likely to be biased to a peculiar form when there are too few triangular samples that are combinations of three polygons. It becomes.

In the eighth aspect of the present invention,
In the database, in addition to the area ratio distribution, a circumscribed circle distribution that is a frequency distribution of the circumscribed circle of the triangle is registered,
The frequency distribution calculating means calculates a circumscribed circle distribution that is a frequency distribution of the circumscribed circle of the triangle in addition to the area ratio distribution for the target model,
The frequency distribution matching means, in addition to the verification of the area ratio distribution, compares the circumscribed circle distribution of the target model with the circumscribed circle distribution of the restriction model, and determines whether or not the output should be regulated. Features.

  According to the eighth aspect of the present invention, in addition to the area ratio distribution, a circumscribed circle distribution that is a frequency distribution of the circumscribed circle of the triangle is registered, and in addition to the area ratio distribution, the target model is registered. A circumscribed circle distribution which is a frequency distribution of the circumscribed circle of the triangle, and in addition to the verification of the area ratio distribution, the circumscribed circle distribution of the target model is verified with the circumscribed circle distribution of the regulatory model, and output Since the polygon model that cannot be specified by the area ratio distribution alone can be narrowed down, whether or not the output should be regulated when outputting a three-dimensional object based on the polygon model. Can be determined with high accuracy using the circumscribed circle distribution that reflects the shape of the polygon model together with the area ratio distribution, and the similarity between the two polygon models can be determined from multiple viewpoints. It becomes possible to perform the determination of whether to regulate the output more accurately. Here, the sharp reflection in the shape of the polygon model has the following meaning. For example, in the sphere that is the basis of the 3D shape, both the area ratio distribution and the circumscribed circle distribution are simple frequency distributions in which a peak appears at one place of the maximum distance corresponding to the radius of the sphere. However, as the 3D shape deviates from the sphere, peaks are added at various locations, and the area ratio distribution and circumscribed circle distribution are different from each other, resulting in a complex frequency distribution that clearly reacts to the shape difference.

In the ninth aspect of the present invention,
In calculating the circumscribed circle distribution, the frequency distribution calculating unit prepares a one-dimensional array composed of a predetermined number of elements, and sets the range of the calculated maximum value of the radius of the circumscribed circle to the predetermined number. After dividing equally, the radius of each circumscribed circle is assigned to one of the predetermined number of elements (md) based on the value of the radius of the circumscribed circle, and the circumscribed circle distribution is determined by the number corresponding to the element. Is calculated.

  According to the ninth aspect of the present invention, in calculating the circumscribed circle distribution, a one-dimensional array composed of a predetermined number of elements is prepared, and the range of the calculated maximum value of the radius of the circumscribed circle is set to the predetermined number. After dividing equally, the radius of each circumscribed circle is assigned to one of a predetermined number of elements based on the value of the radius of the circumscribed circle, and the radius distribution of the circumscribed circle is calculated based on the number corresponding to the element. Therefore, it is possible to calculate a circumscribed circle distribution that reflects sharply the difference in the shape of the triangle.

In the tenth aspect of the present invention,
The frequency distribution calculating means multiplies the area of the polygon by an inner product value of a unit vector from the center of gravity of a triangle formed by a predetermined point of the three polygons to each vertex and a normal vector of the polygon including the vertex. An average value of the obtained values is calculated as a weight value, and weighting is performed using the weight value when obtaining a number corresponding to the element.

  According to the tenth aspect of the present invention, an inner product value of a unit vector from the center of gravity of a triangle formed by a predetermined point of three polygons to each vertex and a normal vector of the polygon including the vertex is calculated as the area of the polygon. The average value of the values multiplied by is calculated as a weight value, and when the number corresponding to the element is obtained, the weight value is used for weighting, so that three polygons are converted into polygon models corresponding to the same part. There is a difference in the frequency distribution calculated between the case where the polygon belongs and the case where the three polygons belong to a polygon model corresponding to a plurality of parts, so that the individual parts in the frequency distribution can be identified more clearly, and the output 3D polygon model Appropriately determine whether output is appropriate, even if the data is output in the form of multiple parts that make up the regulatory model registered in the database Theft is possible.

  In the eleventh aspect of the present invention, the frequency distribution calculating means may calculate the value of each element (Hd () by the sum of weight values (weight sum value SQsum) for each polygon constituting each target model. The frequency distribution is calculated by dividing md) and Ha (ma)) and giving the absolute value when the element is a negative value.

  According to the eleventh aspect of the present invention, in calculating the frequency distribution, the value of each element is divided by the weight value for each polygon constituting each target model, and when the element is a negative value, Since the value is changed to a positive value, the frequency distributions can be easily collated.

In the twelfth aspect of the present invention,
A process of matching the scale of the radius of the circumscribed circle of the frequency distribution of the target model with the scale of the radius of the circumscribed circle of the frequency distribution of the regulatory model registered in the database, and the frequency of the matched target model A frequency distribution matching means for creating a distribution;
The frequency distribution matching unit is configured to match the frequency distribution of the matched target model with the frequency distribution of the restriction model to determine whether or not the output should be restricted.

  According to the twelfth aspect of the present invention, the scale of the radius of the circumscribed circle of the frequency distribution composed of the area ratio distribution or circumscribed circle distribution of the target model is used as the area ratio distribution or circumscribed circle of the restriction model registered in the database. Processing to match the radius of the circumscribed circle of the frequency distribution consisting of the distribution, creating the frequency distribution of the matched target model, the frequency distribution of the matched target model, the area ratio distribution of the regulatory model Alternatively, since the frequency distribution of the circumscribed circle distribution is collated, the scale of the target model and the regulatory model can be matched, and the frequency distribution of the regulatory model represents the characteristics of an object consisting of many parts. In addition, it is possible to perform accurate matching by matching the size with the part represented by the frequency distribution of the target model.

In the thirteenth aspect of the present invention,
With respect to the frequency distribution of the target model and the frequency distribution of the regulation model, the smaller the value of the element, the larger the value and the multiplication of the emphasis component that takes a value greater than 0 and less than or equal to 1, respectively. And a frequency distribution emphasizing means for creating an emphasis frequency distribution of the regulatory model,
The frequency distribution collating unit collates the emphasis frequency distribution of the target model with the emphasis frequency distribution of the restriction model.

  According to the thirteenth aspect of the present invention, with respect to the frequency distribution of the target model and the frequency distribution of the restriction model, the smaller the value of the element, the larger the value, and the emphasis component that takes a value greater than 0 and 1 or less. Multiplying, creating the emphasis frequency distribution of the target model and the emphasis frequency distribution of the regulatory model, and collating the emphasis frequency distribution of the target model with the emphasis frequency distribution of the regulatory model, so from the frequency distribution of the regulatory model, A component that does not correspond to the frequency distribution of the target model can be attenuated and partially verified with the frequency distribution of the restriction model. For this reason, even when the target model corresponds to one component of the restriction model, it is possible to determine with high accuracy whether or not the output should be restricted.

  Further, in the fourteenth aspect of the present invention, the frequency distribution matching means calculates a correlation coefficient between the frequency distributions when matching the frequency distribution of the target model with the frequency distribution of the regulatory model. It is characterized in that it is determined whether or not the output should be regulated based on the correlation coefficient.

  According to the fourteenth aspect of the present invention, when collating the frequency distribution of the target model with the frequency distribution of the restriction model, the correlation coefficient between the frequency distributions is calculated, and the output is regulated based on the calculated correlation coefficient. Because the frequency distribution of the regulatory model represents the characteristics of an object consisting of many parts, the frequency distribution of the target model corresponds to some of the parts in it. Even if it represents, accurate verification can be performed.

  Further, in the fifteenth aspect of the present invention, the frequency distribution matching means calculates peak positions each giving a maximum value when matching the frequency distribution of the target model with the frequency distribution of the regulatory model. It is characterized in that it is determined whether or not the output should be regulated based on a difference between peak positions.

  According to the fifteenth aspect of the present invention, when collating the frequency distribution of the target model with the frequency distribution of the restriction model, the peak position giving the maximum value is calculated, and the output is based on the difference between the calculated peak positions. Since it is determined whether or not it should be regulated, even if the frequency distribution of the regulated model represents the characteristics of an object consisting of many parts, the characteristics corresponding to the parts represented by the frequency distribution of the target model are regulated. It is possible to identify from the frequency distribution of the model and perform accurate matching.

  In the sixteenth aspect of the present invention, the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the restriction model is divided by the square root of the area of the triangle with respect to the restriction model. And a registration means for receiving the area ratio distribution calculated by the regulatory model frequency distribution calculating device for calculating the area ratio distribution which is a frequency distribution based on the value, and registering the received area ratio distribution in the database. And

  According to the sixteenth aspect of the present invention, for the restriction model, a value obtained by dividing the area of the circumscribed circle of the triangle formed by the predetermined points of the three polygons in the restriction model by the square root of the area of the triangle; Since the regulation model frequency distribution calculation device that calculates the area ratio distribution that is a frequency distribution based on the above is prepared separately, the area ratio distribution of the regulation model is received from this regulation model frequency distribution calculation device, and is registered in the database. The database can be updated quickly from a remote location.

In the seventeenth aspect of the present invention,
The regulation model frequency distribution calculating device acquires polygons in the regulation model in units of three for the regulation model, and randomly classifies them into three groups of a first group, a second group, and a third group. The three polygons are selected by selecting one polygon from each group.

  According to the seventeenth aspect of the present invention, polygons in the regulation model are acquired in units of three, and are randomly classified into three groups of the first group, the second group, and the third group, one from each group. Since polygons are selected, a combination of three polygons for forming a triangle can be created without overlapping each other, and efficient processing can be performed. In particular, grouping can be performed in a state free from peculiar wrinkles by acquiring three units and randomly classifying them into groups.

In the eighteenth aspect of the present invention,
Means for outputting the target model to a connected three-dimensional object shaping apparatus;
When it is determined that the output should be regulated (output inappropriate) by the frequency distribution matching unit executed in parallel with the three-dimensional object modeling process by the three-dimensional object modeling apparatus, Means for outputting an output stop command of the target model;
It further has these.

  According to the eighteenth aspect of the present invention, the target model is output to the connected three-dimensional object shaping apparatus, and as a result of collation performed by the frequency distribution collating means executed in parallel, it is determined that the output should be restricted. In this case, since the output stop command for the target model is output to the three-dimensional object modeling apparatus, the output can be canceled only when the output is inappropriate without delaying the modeling of the three-dimensional object that takes time. It becomes possible.

In the nineteenth aspect of the present invention,
The output control terminal and the processing server are connected via a network,
The output control terminal has the frequency distribution calculating means,
The processing server
The database;
Receiving means for receiving an area ratio distribution of the target model from the output control terminal via a network;
The frequency distribution matching means;
Output suitability data transmission means for transmitting data based on whether the output should be regulated or not, determined by the frequency distribution matching means, to the output control terminal;
It is characterized by having.

  According to the nineteenth aspect of the present invention, the area ratio distribution of the target model is received via the network, and the determination result obtained by determining whether the output should be regulated is transmitted to the transmission source of the frequency distribution of the target model. As a result, it is possible to provide the cloud type determination as to whether or not the output should be regulated, and to reduce the processing on the output side. In addition, the database can be centrally managed on the cloud side, and there is no need to manage the database in the output control terminal connected to each 3D object shaping device such as a 3D printer, so the output is always regulated based on the latest database. It is possible to determine whether or not to do so.

In the twentieth aspect of the present invention,
The three-dimensional object shaping data output restriction device;
A three-dimensional object modeling apparatus that models a three-dimensional object using a polygon model whose output is permitted by the three-dimensional object modeling data output restriction device;
There is provided a three-dimensional object forming system.

  According to the twentieth aspect of the present invention, the three-dimensional object modeling data output regulation device and the three-dimensional object modeling device that models the three-dimensional object using the polygon model whose output is permitted by the three-dimensional object modeling data output regulation device. Since the object modeling system is realized, the three-dimensional object modeling system can be provided in the form of a 3D printer or the like incorporating a board computer.

In the twenty-first aspect of the present invention,
A device that calculates a frequency distribution based on the polygon model in order to determine whether or not to regulate when a polygon model expressed as a set of polygons is output to the three-dimensional object modeling apparatus as three-dimensional object modeling data. There,
Based on a target model which is a polygon model to be output, a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the target model by the square root of the area of the triangle Provided is a frequency distribution calculating device for calculating an area ratio distribution which is a frequency distribution.

  According to the twenty-first aspect of the present invention, with respect to a target model that is a polygon model to be output, an area of a circumscribed circle of a triangle formed by predetermined points of three polygons selected from the target model is Since the area ratio distribution, which is a frequency distribution based on the value divided by the square root of the area of the triangle, is calculated, it is possible to calculate the area ratio distribution that accurately represents the shape between the polygons by the triangle and the circumscribed circle. It becomes possible.

  According to a twenty-second aspect of the present invention, there is provided a program for causing a computer to function as the three-dimensional object formation data output restriction device according to any one of the above aspects.

  According to the twenty-second aspect of the present invention, a program for causing a computer to function as a three-dimensional object shaping data output restriction device is provided. By incorporating this program, the computer becomes a three-dimensional object shaping data output restriction device. Function.

  According to the present invention, it is possible to more appropriately determine whether or not the output of the 3D polygon model is appropriate.

It is a figure which shows the relationship between a triangle and a circumscribed circle, and a triangle and an inscribed circle. It is a figure for demonstrating the relationship of the area ratio of a triangle, a circumcircle, and a triangle and a circumcircle. 1 is a hardware configuration diagram of a three-dimensional object formation system including a three-dimensional object formation data output restriction device 100 according to an embodiment of the present invention. It is a functional block diagram which shows the structure of the data output control apparatus for solid object modeling which concerns on one Embodiment of this invention. It is a flowchart which shows the process outline | summary of the data output control apparatus for solid object shaping which concerns on one Embodiment of this invention. It is a figure which shows the mode of collation with a target model (parts) and a regulation model (whole). It is a flowchart which shows the detail of the 1st method of the calculation process of the frequency distribution of step S100. It is a figure for demonstrating the group classification | category of the polygon in this embodiment. It is a figure for demonstrating the group classification | category by the remainder divided by 3 based on the order in a data arrangement | sequence. It is a figure which shows the relationship between the polygon model of 3D shape, and the selected triangle. It is a figure which shows the relationship between the 3D-shaped structural component and the selected triangle in case a mutually congruent triangle is selected. FIG. 12 is a diagram illustrating a relationship between a positional relationship between a triangle and a polygon and a normal vector of the polygon in the same polygon model as in FIG. 11. It is a flowchart which shows the detail of the 2nd method of calculation processing of the frequency distribution of step S100. It is a figure which shows the triangle for calculating | requiring a circumcircle distribution and area ratio distribution, and its circumcircle. It is a figure which shows the mode of a change of the frequency distribution by the emphasis process of the frequency distribution of step S170. It is a flowchart which shows the detail of the collation process of the frequency distribution of step S200. It is a figure which shows the relationship between frequency distribution (histogram) and a peak position. It is a hardware block diagram of the solid object modeling system containing the data output control apparatus for solid object modeling in a modification. It is a hardware block diagram of a cloud type solid thing modeling system. It is a functional block diagram of a cloud type solid thing modeling system. It is a figure which shows a comparative example. It is a figure which shows the collation example 1. FIG. It is a figure which shows the collation example 2. FIG.

<1. Basic concept of the present invention>
First, the basic concept of the present invention will be described. In the above Patent Documents 1 and 2, the distance distribution and the angle distribution are used as the frequency distribution expressing the characteristics of the polygon model. However, as an index that reflects the shape of the polygon model sensitively, an index in the polygon model (3D model) is used. It is conceivable to define a triangle formed by connecting the center of gravity of each of the three polygons, calculate the frequency distribution of the radius of the circumscribed circle as the circumscribed circle distribution, and collate the circumscribed circle distribution. Since the circumscribed circle distribution is more sensitively reflected in the shape of the polygon model than the distance distribution and the angle distribution, it is possible to perform a more accurate collation for determining the output suitability. Since the triangle formed by the predetermined points of the three polygons is a triangle used in calculation to obtain the frequency distribution, it can also be considered as a “provisional triangle”.

  Even if the circumscribed circle has the same radius, the shape of the triangle cannot be specified, and there are infinite variations. Therefore, it is preferable that there is at least another index in order to perform more accurate collation. As this index, it is conceivable to use an inscribed circle distribution which is a frequency distribution of the radius of the inscribed circle. FIG. 1 is a diagram illustrating a relationship between a triangle and a circumscribed circle, and a triangle and an inscribed circle. As shown in FIG. 1A, when the areas of the triangles are the same, the radius of the circumscribed circle is increased by changing the triangle shape from a regular triangle to a flat triangle. Specifically, the time of equilateral triangle is the minimum, and when the shape becomes flat, the radius approaches infinity. That is, the range of change of the circumscribed circle radius with respect to the triangular shape is infinite and large.

  On the other hand, as shown in FIG. 1B, when the areas of the triangles are the same, the radius of the inscribed circle becomes smaller by changing the triangle shape from a regular triangle to a flat triangle. . Specifically, the maximum is a regular triangle, and the radius approaches 0 when the shape becomes flat. That is, the change width of the inscribed circle radius with respect to the triangular shape is finite and small.

  Consider the case of using an area ratio distribution which is a frequency distribution based on a value obtained by dividing the area of the circumscribed circle by the square root of the area of the triangle instead of the inscribed circle radius. FIG. 2 is a diagram for explaining the relationship between the triangle, its circumscribed circle, and the area ratio between the triangle and the circumscribed circle. FIG. 2A is the same as FIG. As described above, when the areas of the triangles are the same, the radius of the circumscribed circle is increased by changing the shape of the triangle from a regular triangle to a flat triangle. Specifically, the time of equilateral triangle is the minimum, and when the shape becomes flat, the radius approaches infinity. That is, the range of change of the circumscribed circle radius with respect to the triangular shape is infinite and large. However, there are an infinite number of triangles having the same circumscribed circle radius, and the triangle cannot be specified only by the circumscribed circle radius.

  Therefore, as shown in FIG. 2B, if the shape of the triangle is changed from a regular triangle to a flat triangle under the condition that the radius of the circumscribed circle is the same, the area of the circumscribed circle is reduced to the area of the triangle. The area ratio, which is the value divided by the square root, increases. Specifically, when the regular triangle is the smallest and the shape becomes flat, the area ratio approaches infinity. That is, the range of change in the area ratio with respect to the triangular shape is infinite and large as is the radius of the circumscribed circle. Therefore, when another index is used together with the circumscribed circle distribution, the area ratio distribution is preferable to the inscribed circle distribution that reacts oppositely to the circumscribed circle radius. Therefore, in the present invention, an area ratio distribution, which is a frequency distribution based on a value obtained by dividing the area of the circumscribed circle by the square root of the area of the triangle, is used as an object to be verified. However, in order to match the dimension with the circumscribed circle radius, the area ratio used in the area ratio distribution is preferably a length (distance) dimension. Therefore, the area ratio distribution used in the present embodiment is not an area ratio in an accurate sense obtained by dividing the area of the circumscribed circle by the area of the triangle itself, but the square of the radius of the circumscribed circle (the area of the circumscribed circle is represented by π). The “pseudo area ratio” which is a value obtained by dividing the divided area by the square root of the area of the triangle is treated as an “area ratio”, and the frequency distribution is called an “area ratio distribution”. Eventually, the area ratio distribution may be any one that reflects the ratio of the area of the circumscribed circle and the area of the triangle in some manner. Therefore, “the value based on the area of the circumscribed circle of the triangle divided by the square root of the area of the triangle” includes “the square of the radius of the circumscribed circle (the area of the circumscribed circle divided by π)”. , A value divided by the square root of the area of the triangle ”.

DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described in detail with reference to the drawings.
<2. Device configuration>
FIG. 3 is a hardware configuration diagram of a three-dimensional object formation system including the three-dimensional object formation data output restriction device 100 according to an embodiment of the present invention. The three-dimensional object modeling data output restriction device 100 according to the present embodiment can be realized by a general-purpose computer. As shown in FIG. 3, a CPU (Central Processing Unit) 1 and a RAM (a main memory of the computer) Random Access Memory) 2, a large-capacity storage device 3 such as a hard disk or flash memory for storing programs and data executed by the CPU 1, a key input I / F (interface) 4 such as a keyboard and a mouse, and 3D A data input / output I / F (interface) 5 for data communication with an external device such as a printer or a data storage medium and a display unit 6 which is a display device such as a liquid crystal display are connected to each other via a bus. ing.

  The 3D printer 7 is a general-purpose 3D printer, which processes a material such as resin and gypsum on the basis of data for modeling a three-dimensional object, which is a polygon model expressing the three-dimensional shape of the three-dimensional object as a set of polygons. It is a three-dimensional object modeling apparatus to model. The 3D printer 7 includes a data processing unit 7a and an output unit 7b. The data processing unit 7a of the 3D printer 7 is connected to the data input / output I / F 5 so that the output unit 7b models the three-dimensional object based on the three-dimensional object modeling data received from the data input / output I / F 5. It has become.

  In FIG. 3, the three-dimensional object formation data output restriction device 100 and the 3D printer 7 are shown in a separated form, but most of the 3D printer products currently on the market include the three-dimensional object formation data output restriction device 100. Constituent elements, such as CPU1, RAM2, storage device 3, key input I / F4 (not a keyboard / mouse for general-purpose computers, but several buttons at a numeric keypad level), data input / output I / F5, display unit 6 (several lines) A small liquid crystal panel or a touch panel capable of displaying the above characters is often used as a key input I / F 4 in an overlapping manner. Accordingly, the 3D printer 7 itself can directly receive the three-dimensional object modeling data via the external storage medium, and can be operated to model the three-dimensional object alone (particularly this is more common in a 3D printer for consumer use). ). That is, the three-dimensional object modeling system shown in FIG. 3 is often housed in one housing and distributed as a product called “3D printer”.

  FIG. 4 is a functional block diagram illustrating a configuration of the three-dimensional object formation data output restriction device according to the present embodiment. In FIG. 4, 10 is a frequency distribution calculating means, 20 is a frequency distribution matching means, 30 is a frequency distribution emphasizing means, 40 is a frequency distribution matching means, 50 is a target model storage means, and 60 is a regulation model database. The frequency distribution calculating means 10 calculates a parameter characterizing a triangle formed by points of the center of gravity on three polygons selected from within the target model for the target model which is a polygon model to be output, and the parameter Calculate the frequency distribution. In the present embodiment, two types of parameters, a first parameter and a second parameter, are used as parameters. More specifically, the radius of the circumscribed circle of a triangle formed by the center of gravity of three polygons selected from within the target model is used as the first parameter, and the radius is selected from within the target model as the second parameter. An area ratio that is a value obtained by dividing the area of the circumscribed circle of the triangle formed by the points of the center of gravity of the three polygons by the square root of the area of the triangle is used. Therefore, the frequency distribution calculating means 10 is a value obtained by dividing the circumscribed circle distribution which is the frequency distribution of the radius of the circumscribed circle as the first frequency distribution and the area of the circumscribed circle as the second frequency distribution by the square root of the area of the triangle. Two types of frequency distribution of the area ratio distribution, which is the frequency distribution of the area ratio, are calculated.

  The frequency distribution matching unit 20 performs processing for matching the scale of the horizontal axis parameter of the frequency distribution of the target model with the scale of the horizontal axis parameter of the frequency distribution of the regulatory model registered in the database. The maximum value on the horizontal axis of the frequency distribution is normalized by the square of the maximum value of the circumscribed circle radius calculated for each model or the maximum value of the circumscribed circle radius. The horizontal scales of do not usually match. Therefore, when the frequency distribution matching unit 20 outputs each of the target model and the restriction model by the 3D printer, the actual dimension corresponding to the maximum value on the horizontal axis of the frequency distribution of the target model is the actual dimension α, and the frequency of the restriction model. When the actual dimension corresponding to the maximum value on the horizontal axis of the distribution is the actual dimension β, the frequency distribution is reduced in the horizontal direction so that the horizontal axis of the frequency distribution of the target model is reduced by the actual dimension α / actual dimension β. I do. The frequency distribution consists of a circumscribed circle distribution and an area ratio distribution, both of which are normalized using the maximum value of the circumscribed circle radius (the area ratio distribution uses the square of the maximum value) The scales of the two horizontal axes coincide with each other, and both frequency distributions may be reduced by the actual dimension α / the actual dimension β. The frequency distribution emphasizing unit 30 multiplies the frequency distribution of the matched target model and the frequency distribution of the restriction model by the emphasis component, respectively, and creates the enhancement frequency distribution of the target model and the enhancement frequency distribution of the restriction model. As the enhancement frequency distribution, as described above, two types of enhancement frequency distributions are calculated: a circumscribed circle distribution that is a frequency distribution of the radius of the circumscribed circle and an area ratio distribution that is a frequency distribution of the area ratio. The frequency distribution collating means 40 collates the enhancement frequency distribution calculated for the target model with the enhancement frequency distribution calculated for the restriction model, and whether or not the output should be regulated, that is, whether the output is inappropriate or appropriate. Determine.

  The frequency distribution calculating unit 10, the frequency distribution matching unit 20, the frequency distribution emphasizing unit 30, and the frequency distribution matching unit 40 are realized by the CPU 1 executing a program stored in the storage device 3. The target model storage unit 50 is a storage unit that stores a target model that is a polygon model that is a determination target of whether or not to restrict output, and is realized by the storage device 3. The polygon model is data representing a predetermined three-dimensional shape in a three-dimensional space by a set of polygons, and is output as three-dimensional object modeling data to a three-dimensional object modeling apparatus such as a 3D printer. In this embodiment, STL (Standard Triangulated Language) is adopted as the data format of the polygon model.

  The restriction model database 60 stores a circumscribed circle distribution and an area ratio distribution calculated as two types of frequency distributions with respect to a restriction model which is a polygon model whose output is to be restricted, and is a database. 3 is realized. The circumscribed circle distribution and the area ratio distribution, which are two kinds of frequency distributions, serve as feature data expressing the features of the regulation model. That is, the difference between the original restriction models can be identified by the two types of frequency distributions, but the original restriction model cannot be restored. This is similar to the fact that individual differences can be identified by fingerprints, but the figure of the person itself cannot be restored. Therefore, the two frequency distributions do not play a role as a work, but also play a role as a so-called fingerprint that proves the identity of the two works. In the regulation model database 60, it is possible to register not only the circumscribed circle distribution and the area ratio distribution but also the regulation model itself that is a basis for calculating the circumscribed circle distribution and the area ratio distribution. The regulatory model itself is not registered due to copyright issues.

  Each component shown in FIG. 4 is actually realized by installing a dedicated program in hardware such as a computer and its peripheral devices as shown in FIG. That is, the computer executes the contents of each means according to a dedicated program. In this specification, the computer means an apparatus having an arithmetic processing unit such as a CPU and capable of data processing, and is incorporated not only in a general-purpose computer such as a personal computer but also in a “3D printer” as a product. Board computer included.

  In the storage device 3 shown in FIG. 3, a dedicated program for operating the CPU 1 and causing the computer to function as a three-dimensional object formation data output restriction device is mounted. By executing this dedicated program, the CPU 1 realizes functions as the frequency distribution calculating means 10, the frequency distribution matching means 20, the frequency distribution emphasizing means 30, and the frequency distribution matching means 40. The storage device 3 not only functions as the target model storage unit 50 and the restriction model database 60 but also stores various data necessary for processing as the three-dimensional object formation data output restriction device.

  In the hardware configuration shown in FIG. 3, the frequency distribution calculating device for calculating the frequency distribution is implemented by mounting only a dedicated program for causing the computer to function as the frequency distribution calculating means 10 in the storage device 3. Can also be realized. The frequency distribution calculation device calculates and outputs two types of frequency distributions based on the target model read from the target model storage unit 50. The output frequency distribution is separately input to an apparatus including a frequency distribution matching unit 20, a frequency distribution emphasizing unit 30, a frequency distribution matching unit 40, and a regulation model database 60, and can be used for collation and output regulation determination. .

<3. Processing action>
<3.1. Pretreatment>
Next, the processing operation of the three-dimensional object formation data output restriction device shown in FIGS. 3 and 4 will be described. First, a circumscribed circle distribution and an area ratio distribution, which are two types of frequency distributions, are created for a restriction model that is a polygon model to be restricted. Creation of the circumscribed circle distribution and the area ratio distribution from the polygon model can be performed in the same manner as the processing in the three-dimensional object formation data output restriction device described later. Creation of the circumscribed circle distribution and the area ratio distribution from the restriction model may be performed by the three-dimensional object formation data output restriction device, or may be performed by executing a similar program on another computer. The created circumscribed circle distribution and area ratio distribution are registered in the regulation model database 60.

  The target of output regulation may be not only dangerous materials such as guns and swords, but also copyrighted materials such as characters. In any case, the produced polygon model becomes a copyrighted work with a copyright holder. Therefore, in order to register a polygon model, which is a work, in the database, permission for the author is required for the act itself. Differences in the original polygon model can be identified by the forms of the circumscribed circle distribution and the area ratio distribution, but the original polygon model cannot be restored. This is similar to the fact that individual differences can be identified by fingerprints, but the figure of the person itself cannot be restored, and the circumscribed circle distribution and area ratio distribution form correspond to fingerprints. This is not a copyrighted work. Thus, by registering in the form of circumscribed circle distribution and area ratio distribution as in the present invention, it is possible to construct a database that records the characteristics of the regulatory model without requiring the author's permission.

<3.2. Process Overview>
Next, the processing operation of the three-dimensional object formation data output restriction device shown in FIGS. 3 and 4 will be described. FIG. 5 is a flowchart showing a processing outline of the three-dimensional object formation data output restriction device according to the embodiment of the present invention. First, the frequency distribution calculating means 10 calculates a circumscribed circle distribution and an area ratio distribution, which are two types of frequency distributions, for the target model that is a polygon model (step S100). Next, the calculated two types of frequency distributions are matched using the frequency distribution of the restriction model registered in the restriction model database 60 (step S130). Further, using the emphasis component, emphasis processing of the two types of frequency distributions created in step S130 is performed (step S170). Then, the enhancement frequency distribution of the target model subjected to the enhancement process is collated with the enhancement frequency distribution of the restriction model subjected to the enhancement process (step S200).

  The manner in which the two polygon models are collated by the processing shown in FIG. 5 will be described with reference to FIG. FIG. 6 is a diagram illustrating a state of matching between the target model and the restriction model. In the example of FIG. 6, the whole is registered as a restriction model (1) in the database, and a part of the restriction model (1) is used as the target model (2). In this case, two kinds of frequency distributions (3) are obtained from the restriction model (1) and two kinds of frequency distributions (4) are obtained from the target model (2) by the process of step S100. At this time, the horizontal axis of the frequency distribution indicates the maximum circumscribed circle radius (described later as maximum radius a and maximum radius b in FIG. 6) and does not reflect the scale at the time of 3D printer output. And the scale of the maximum circumscribed circle radius is greatly different. Therefore, the process of step S130 performs the process of matching the frequency distribution of the target model with the frequency distribution of the restriction model using the actual maximum circumscribed circle radius (5). Specifically, when each of the target model and the regulated model is output by the 3D printer, the actual dimension α of the maximum circumscribed circle radius of the target model is the actual dimension α, and the actual dimension of the maximum circumscribed circle radius of the regulated model is the actual dimension β. , The frequency distribution is reduced in the horizontal direction so that the horizontal axis of the frequency distribution of the target model is the actual dimension α / the actual dimension β (maximum radius b / maximum radius a). The frequency distribution is composed of a circumscribed circle distribution and an area ratio distribution, but the scales of the horizontal axes are the same, so both frequency distributions are reduced so that the horizontal axis is the actual dimension α / actual dimension β. You can do it. Thereafter, an emphasis component is created (6), the emphasis process is performed (7) (8), and then a collation process is performed (9).

<3.3. Frequency distribution calculation processing>
The frequency distribution calculation process (step S100) will be specifically described below. There are two types of frequency distribution calculation processing: the first method and the second method.
<3.3.1. First Method>
First, the first method will be described. FIG. 7 is a flowchart showing details of the frequency distribution calculation processing by the first method. Here, the number of polygons of the target model is N, and the variable i (i = 0,..., N−1) for specifying the polygon is used, and the vertices of each polygon i are (Xu (i), Yu (i), Zu ( i)), the normal vector of each polygon i is defined as (Xn (i), Yn (i), Zn (i)). u indicates a vertex number. In this embodiment, since the polygon is triangular, three values of u = 0, 1, and 2 are taken. Therefore, for example, Xu (i) is also expressed as X0 (i), X1 (i), and X2 (i). The polygons and normal vectors specifying the vertices are necessary for output by a 3D printer, which is a three-dimensional object forming apparatus, and the direction of the normal vectors indicates the outside of the forming surface (from the material to the air). The normal vector is normally recorded for each polygon in a polygon model for output to a 3D printer. The target model also has its output scale information Sout. The output scale information Sout is an actual dimension when the target model is output as a three-dimensional object, and is an actual dimension per unit length (length 1) of the three-dimensional coordinate system defining the vertex, expressed in mm. Has been. First, the frequency distribution calculating means 10 calculates the area Sp (i) of each polygon i constituting the target model by executing processing according to the following [Equation 1] (step S501).

[Formula 1]
Vx (i) = [Y1 (i) -Y0 (i)] [Z2 (i) -Z0 (i)]-[Z1 (i) -Z0 (i)] [Y2 (i) -Y0 (i)]
Vy (i) = [Z1 (i) -Z0 (i)] [X2 (i) -X0 (i)]-[X1 (i) -X0 (i)] [Z2 (i) -Z0 (i)]
Vz (i) = [X1 (i) -X0 (i)] [Y2 (i) -Y0 (i)]-[Y1 (i) -Y0 (i)] [X2 (i) -X0 (i)]
Sp (i) = [Vx (i) ² + Vy (i) ² + Vz (i) ² ] ^1/2

  Next, for each polygon constituting the target model, the gravity center of the polygon is calculated (step S502). Specifically, by executing the processing according to the following [Equation 2], the center of gravity (Xc (i), Yc (i), Zc (i)) of the polygon having the average coordinates of the vertices of each polygon is obtained. calculate.

[Formula 2]
Xc (i) = {X0 (i) + X1 (i) + X2 (i)} / 3
Yc (i) = {Y0 (i) + Y1 (i) + Y2 (i)} / 3
Zc (i) = {Z0 (i) + Z1 (i) + Z2 (i)} / 3

  In the above [Equation 2], X0 (i), X1 (i), and X2 (i) represent the cases of vertex numbers u = 0, 1, and 2 in Xu (i), respectively, and Y0 (i), Y1 ( i) and Y2 (i) respectively indicate the cases of vertex numbers u = 0, 1, and 2 in Yu (i), and Z0 (i), Z1 (i), and Z2 (i) are in Zu (i), respectively. , Vertex numbers u = 0, 1, and 2 are shown. As shown in the above [Equation 2], the polygon centroid is calculated as a point having the average coordinates of each vertex of the polygon.

  Here, the center of gravity of the triangle and the unit vector to each vertex of the triangle will be described. The centroid of a triangle formed by the polygon centroids of three polygons i1, i2, i3 (i1, i2, i3 are different integers with i ranging from 0 to N-1) (Xo (i1, i2, i3 ), Yo (i1, i2, i3), Zo (i1, i2, i3)). That is, the center of gravity of the triangle (Xo (i1, i2, i3), Yo (i1, i2, i3), Zo (i1, i2, i3)) is defined by the following [Equation 3].

[Formula 3]
Xo (i1, i2, i3) = {Xc (i1) + Xc (i2) + Xc (i3)} / 3
Yo (i1, i2, i3) = {Yc (i1) + Yc (i2) + Yc (i3)} / 3
Zo (i1, i2, i3) = {Zc (i1) + Zc (i2) + Zc (i3)} / 3

  Then, by the following [Equation 4], unit vectors (Ex (i2, i3, i1), Ey) from the centroid of the triangle to the polygon centroid (Xc (i1), Yc (i1), Zc (i1)) of the polygon i1 (I2, i3, i1), Ez (i2, i3, i1)) are defined.

[Formula 4]
E (i2, i3, i1) = [{Xc (i1) −Xo (i1, i2, i3)} ² + {Yc (i1) −Yo (i1, i2, i3)} ² + {Zc (i1) − Zo (i1, i2, i3)} ² ] ^1/2
Ex (i2, i3, i1) = {Xc (i1) -Xo (i1, i2, i3)} / E (i2, i3, i1)
Ey (i2, i3, i1) = {Yc (i1) −Yo (i1, i2, i3)} / E (i2, i3, i1)
Ez (i2, i3, i1) = {Zc (i1) −Zo (i1, i2, i3)} / E (i2, i3, i1)

  The center vector of the triangle and the unit vector to each vertex of the triangle are used for calculating the frequency distribution in step S508, which will be described later, by executing the processing according to the above [Equation 3] and [Equation 4].

  Next, a set of polygons constituting the polygon model is divided into three groups, and the order of the polygons in each group is changed (step S503). As a method of dividing into three groups, any method may be used as long as it can be divided into the same number. In the present embodiment, as a particularly preferable aspect, grouping is performed at random in units of three based on the order in the data arrangement of the polygon model.

  Specifically, a polygon is acquired in units of three from a set of polygons constituting a polygon model, and the first group, the second group are based on random numbers that randomly generate an integer of 0 to 2, which is the remainder of 3. And classify into any one of the third groups. Then, this process is repeatedly executed for all the polygons constituting the polygon model, thereby dividing the N polygons constituting the polygon model into N / 3 groups. The random number does not necessarily have to be 0 to 2 as long as a state that occurs with a probability of 1/3 can be realized.

  When the remainder of 3 of the original polygon number N is 2 so that the number of polygons in each group is the same, the top polygon 0 is overlapped as the last polygon N = polygon 0, and the total number of polygons is Modify to be N + 1. If the remainder of 3 of the original polygon number N is 1, the first polygon 0 and the second polygon 1 are overlapped as the second polygon N = polygon 0 from the tail and the last polygon N + 1 = polygon 1 In any case, the total number of polygons is corrected to N + 2. Even if the number of polygons is duplicated and the total number of polygons is N + 1 or N + 2 so that the number of polygons in each group is the same, the total number of polygons will be replaced with N in the following. I will explain.

  By grouping by the remainder divided by 3, three arrays G1 (h) = 3h + Q0 (q), G2 (h) = 3h + Q1 (q), G3 (h) = 3h + Q2 (q) (h = 0,. .., N / 3-1) is obtained. Here, the integer value q (q = 0,..., N / 3-1) is given the same value as the integer value h given to G1 (h), and Q0 (q), Q1 (q), Q2 (Q) takes any integer value of {0, 1, 2} based on the integer value q. That is, Q0 (q) = q mod 3, Q1 (q) = (q + 1) mod 3, and Q2 (q) = (q + 2) mod 3 (“mod 3” represents a remainder of 3). As will be described later, since the integer value q is given randomly, Q0 (q), Q1 (q), and Q2 (q) do not overlap each other, and any integer value of {0, 1, 2} is randomly assigned. Take.

  Next, the arrangement order of the polygons in each group is changed. The order is changed randomly. That is, it is shuffled. Any method may be used as long as the order of polygon arrangement can be changed. In this embodiment, the order of polygon arrangement is changed by the following method. First, three types of random number arrays R1 (k), R2 (k), and R3 (k) are created. Specifically, k = 0,..., N / 3-1 are initialized to R1 (k) = k. Subsequently, a real-valued uniform random number is generated N / 3 times within a range of 0 ≦ Rnd (k) <1, and every time it is generated, pp = Rnd (k) × N / 3 is calculated as 0 ≦ An integer value of pp ≦ N / 3-1 is calculated, and the process of exchanging the value of R1 (k) and the value of R1 (pp) is repeated N / 3 times. As a result of repetition, a random number array R1 (k) in which N / 3 consecutive integers are randomly replaced is obtained. Accordingly, for example, h = q = R1 (k) is given to the polygon array G1 (h) of the first group, and G1 (R1 (k)) = 3R1 (k) + Q0 (R1 (k)) As in (k = 0,..., N / 3-1), an array in which the order is changed can be obtained. The second random number array R2 (k) is given by R2 (k) = R1 (N / 3-1-k). That is, the random number array R2 (k) is obtained by reversing the order from the beginning to the end of the first random number array R1 (k). The random number array R1 (k) and the random number array R2 (k) are the other inverted random number arrays. Further, for the third random number array R3 (k), the random number array R3 (k) = k is set to a sequential value of k = 0,. In this way, by rearranging the polygon arrangement order, the polygon arrangement order of each group can be set randomly from the polygons in the target model that is a three-dimensional space, and a combination of points on the random polygons. The circumscribed circle distribution and the area ratio distribution can be obtained based on the area of the triangle and the radius of the circumscribed circle of the triangle (the area of the circumscribed circle is given by the square of the radius of the circumscribed circle). Accordingly, h = R2 (k) and q = R1 (k) are given to the polygon array G2 (h) of the second group, and G2 (R2 (k)) = 3R2 (k) + Q1 (R1 (k )), And h = R3 (k) and q = R1 (k) are given to the polygon array G3 (h) of the third group, and G3 (R3 (k)) = 3R3 (k) + Q2 (R1) (K)) and an array in which the order of the three groups is exchanged can be obtained. As will be described later, h = q = R2 (k) may be given to the polygon array G1 (h) of the first group, and G1 (R2 (k)) = 3R2 (k) + Q0 (R2 ( It is also possible to obtain an array in which the order is changed as in k)).

  The reason why the polygons are classified into the three groups in this way is to prevent the polygons from overlapping each other when the three polygons are randomly selected to create a triangle. Although it is possible to sequentially form triangles by combining all polygons constituting the polygon model, if the number of polygons is large, the number of combinations becomes enormous, which is not practical. A method of forming a triangle by randomly selecting three polygons from all the polygons constituting the polygon model without grouping is also conceivable, but the same triangle is generated with a certain probability. If the number of triangle samples extracted at random is not large enough, a biased frequency distribution may be calculated. As in this embodiment, the three polygons for forming a triangle are overlapped with each other by classifying into three groups, selecting one polygon from each group and selecting a total of three. It is possible to select efficiently while providing randomness.

  FIG. 8 is a diagram for explaining group classification of polygons in the present embodiment. For example, as shown in FIG. 8, it is assumed that nine original polygon arrays (a set of polygons) P1 to P9 are classified into three groups of A group, B group, and C group. In this case, the first three polygons P1, P2, and P3 are classified into an A group, a B group, and a C group, respectively, based on a random number of [0, 1, 2], and the next three polygons P4, P5. , P6 are classified into a B group, a C group, and an A group based on a random number of [1, 2, 0], respectively, and the last three polygons P7, P8, and P9 are random numbers of [2, 0, 1]. Are classified into C group, A group, and B group, respectively. Then, the arrangement order of the polygons in each group is changed (shuffled). As a result, a triangle formed by the polygons P6, P9, and P3, a triangle formed by the polygons P1, P2, and P5, and a triangle formed by the polygons P8, P4, and P7 are obtained.

  FIG. 9 illustrates group classification based on whether the remainder is 0, 1 or 2 divided by 3 based on the order in the polygon model data array, rather than determining groups based on random numbers. FIG. For example, as shown in FIG. 9, it is assumed that nine original polygon arrays (a set of polygons) P1 to P9 are classified into three groups of A group, B group, and C group. In this case, the first three polygons P1, P2, and P3 are classified into an A group, a B group, and a C group based on the remainder [0, 1, 2] obtained by dividing the integer part by 3, respectively. Three polygons P4, P5, and P6 are classified into A group, B group, and C group, respectively, based on the remainder [0, 1, 2] obtained by dividing the integer part by 3, and the last three polygons P7 , P8, and P9 are classified into A group, B group, and C group, respectively, based on the remainder [0, 1, 2] obtained by dividing the integer part by 3. Then, the arrangement order of the polygons in each group is changed (shuffled). As a result, a triangle composed of polygons P4, P8, and P3, a triangle composed of polygons P1, P2, and P6 and a triangle composed of polygons P7, P5, and P9 are obtained. As shown in FIG. 9, when grouping is performed based on the remainder divided by 3, as shown in FIG. A habit will occur.

  Next, initial setting is performed (step S504). Specifically, initialization of the circumscribed circle distribution and area ratio distribution to be calculated, initialization of the loop counter, and initialization of the weight sum value are performed. The circumscribed circle distribution calculated in the present embodiment is a distribution of the radius of a triangular circumscribed circle obtained by weighting the area of the polygon. The number of elements is MD, and each element md (md = 0,..., MD− The frequency of 1) is expressed as Hd (md). Hd (md) is a one-dimensional array composed of a predetermined number of MD elements. An arbitrary value can be set as the number of elements MD, but in this embodiment, MD = 360. After preparing such a one-dimensional array, the frequency distribution calculating means 10 sets the initial value as Hd (md) = 0. The area ratio distribution calculated in the present embodiment is a distribution of a triangle, a circumscribed circle of a triangle, and a ratio of the respective areas weighted with the area of the polygon. The number of elements is MA, and each element ma (ma = 0, ma = 0, ..., the frequency of MA-1) is expressed as Ha (ma). Ha (ma) is a one-dimensional array composed of a predetermined number of elements. The element number MA may be the same as or different from the element number MD. Although an arbitrary value can be set as the element number MA, in the present embodiment, it is the same as the element number MD, and MA = 360. After preparing such a one-dimensional array, the frequency distribution calculating means 10 sets the initial value as Ha (ma) = 0. For the loop counter LC, an initial value LC = 0 is set. Further, the weight sum value SQsum = 0, which is the sum value of the weight values SQ, is set.

  Next, the frequency distribution calculation unit 10 creates a triangle having the centroid of each polygon between the three groups as a vertex (step S505). When creating a triangle using three polygons, various points can be used as points on the polygon, not limited to the center of gravity of the polygon. However, since the polygon centroid is preferable as a point representing one polygon, in this embodiment, a triangle is created with the polygon centroid as a vertex. The point on the polygon means a point located on a plane passing through all the vertices constituting the polygon (a point located outside the triangle like an outer center). In step S505, three combinations are created by changing the combinations between groups so that the number of triangles is the same as the total number N of polygons. Specifically, assuming that q = R1 (k), the order k (k = 0,..., N) in which the order of the polygon G1 (h) of the first group is randomly changed by the random number array R1 (k). / 3-1) the center of gravity of the polygon G1 (R1 (k)) (Xc (G1 (R1 (k))), Yc (G1 (R1 (k))), Zc (G1 (R1 (k)))) , The center of gravity (Xc (G2 (R2 (k)) of the polygon G2 (R2 (k)) in the corresponding order k obtained by randomly changing the order of the polygon G2 (h) in the second group by the random number array R2 (k). )), Yc (G2 (R2 (k))), Zc (G2 (R2 (k)))), and the third group of polygons G3 (h), the order is randomly changed by the random number array R3 (k). The center of gravity (Xc (G3 (R3 ( ))), Yc (G3 (R3 (k))), Zc (G3 (R3 (k)))) a first triangle to N / 3 pieces created whose vertices three points.

  Similarly, as q = R2 (k), the center of gravity of the polygon G1 (R2 (k)) in the order k obtained by randomly changing the order of the first group of polygons G1 (h) by the random number array R2 (k) ( Xc (G1 (R2 (k))), Yc (G1 (R2 (k))), Zc (G1 (R2 (k)))), the second group of polygons G2 (h), a random number array R3 ( k), the center of gravity (Xc (G2 (R3 (k))), Yc (G2 (R3 (k))), Zc (G2) (R3 (k)))), the center of gravity of the polygon G3 (R1 (k)) of the corresponding order k obtained by randomly changing the order of the third group of polygons G3 (h) by the random number array R1 (k) ( Xc (G3 (R1 (k))), Yc (G3 (R1 (k))) , Zc (G3 (R1 (k)))) a second triangle N / 3 pieces created whose vertices three points.

  Further, assuming that q = R3 (k), the center of gravity (Xc) of the polygon G1 (R3 (k)) in the order k obtained by randomly changing the order of the polygon G1 (h) in the first group by the random number array R3 (k). (G1 (R3 (k))), Yc (G1 (R3 (k))), Zc (G1 (R3 (k)))), the second group of polygons G2 (h), a random number array R1 (k ) At the center of gravity (Xc (G2 (R1 (k))), Yc (G2 (R1 (k))), Zc (G2 () R1 (k)))), the center of gravity (Xc) of the polygon G3 (R2 (k)) of the corresponding order k, which is randomly changed in order by the random number array R2 (k) with respect to the polygon G3 (h) of the third group (G3 (R2 (k))), Yc (G3 (R2 (k)) , Zc (G3 (R2 (k)))) the third triangle to N / 3 pieces created as vertices the three points.

  Next, the frequency distribution calculation means 10 calculates the radius of a circumscribed circle of a triangle having the polygon centroid as a vertex (step S506). Specifically, first, by executing the processing according to the following [Formula 5], the area S (k) of the first triangle is set in the range of k = 0,..., N / 3-1. calculate.

[Formula 5]
As q = R1 (k),
D12 = [[Xc (G2 (R2 (k)))-Xc (G1 (R1 (k)))] ² + [Yc (G2 (R2 (k)))-Yc (G1 (R1 (k))) ] ² ] ^1/2
D23 = [[Xc (G3 (R3 (k))) − Xc (G2 (R2 (k)))] ² + [Yc (G3 (R3 (k))) − Yc (G2 (R2 (k))) ] ² ] ^1/2
D31 = [[Xc (G1 (R1 (k))) − Xc (G3 (R3 (k)))] ² + [Yc (G1 (R1 (k))) − Yc (G3 (R3 (k))) ] ² ] ^1/2
D = (D12 + D23 + D31) / 2
S (k) = [D · (D−D12) · (D−D23) · (D−D31)] ^1/2

  In the above [Formula 5], “·” indicates multiplication. The same applies to the following [Formula]. Then, by executing the processing according to the following [Equation 6], the radius D (k) of the circumscribed circle of the first triangle is calculated in the range of k = 0,..., N / 3-1. .

[Formula 6]
D (k) = D12 · D23 · D31 / (4 · S (k))

  Similarly, the frequency distribution calculating means 10 executes a process according to the following [Equation 7], whereby the area S (2) of the second triangle in the range of k = 0,..., N / 3-1. k) is calculated.

[Formula 7]
As q = R2 (k),
D23 = [[Xc (G3 (R1 (k))) − Xc (G2 (R3 (k)))] ² + [Yc (G3 (R1 (k))) − Yc (G2 (R3 (k))) ] ² ] ^1/2
D31 = [[Xe (G1 (R2 (k))) − Xc (G3 (R1 (k)))] ² + [Yc (G1 (R2 (k))) − Yc (G3 (R1 (k))) ] ² ] ^1/2
D12 = [[Xc (G2 (R3 (k))) − Xc (G1 (R2 (k)))] ² + [Yc (G2 (R3 (k))) − Yc (G1 (R2 (k))) ] ² ] ^1/2
D = (D12 + D23 + D31) / 2
S (k) = [D · (D−D12) · (D−D23) · (D−D31)] ^1/2

  Then, the radius D (k) of the circumscribed circle of the second triangle is calculated in the range of k = 0,..., N / 3-1 by executing the processing according to the above [Equation 6]. Similarly, the frequency distribution calculating means 10 executes the process according to the following [Equation 8], whereby the area S (3) of the third triangle in the range of k = 0,..., N / 3-1. k) is calculated.

[Formula 8]
As q = R3 (k),
D31 = [[Xc (G1 (R3 (k))) − Xc (G3 (R2 (k)))] ² + [Yc (G1 (R3 (k))) − Yc (G3 (R2 (k))) ] ² ] ^1/2
D12 = [[Xc (G2 (R1 (k))) − Xc (G1 (R3 (k)))] ² + [Yc (G2 (R1 (k))) − Yc (G1 (R3 (k))) ] ² ] ^1/2
D23 = [[Xc (G3 (R2 (k))) − Xc (G2 (R1 (k)))] ² + [Yc (G3 (R2 (k))) − Yc (G2 (R1 (k))) ] ² ] ^1/2
D = (D12 + D23 + D31) / 2
S (k) = [D · (D−D12) · (D−D23) · (D−D31)] ^1/2

  Then, by executing the processing according to the above [Equation 6], the radius D (k) of the circumscribed circle of the third triangle is calculated in the range of k = 0,..., N / 3-1. In the above [Equation 5], [Equation 7] and [Equation 8], only the triangle in which the lengths D12, D23 and D31 of each side of the triangle satisfy all the six conditions shown in the following [Equation 9] The target of the frequency distribution of the radius. Therefore, a triangle that does not satisfy even one of the six conditions shown in [Formula 9] is not subject to the frequency distribution of the circumscribed circle radius. This is because when the six conditions shown in [Equation 9] below are not satisfied, the radius D (k) of the circumscribed circle becomes extremely large, and a highly accurate frequency distribution cannot be obtained.

[Formula 9]
D12> 0
D23> 0
D31> 0
| D12-D23-D31 | / D12> 0.1
| D23-D31-D12 | / D23> 0.1
| D31-D12-D23 | / D31> 0.1

  As shown in the above [Equation 9], the first three conditions out of the six conditions mean that all sides have positive values other than 0, that is, form a triangle. The latter half of the six conditions means that the triangle to be created does not have an extremely flat shape. If the triangle becomes extremely flat, the radius of the circumscribed circle will approach infinity, and a highly accurate frequency distribution will not be obtained. When the six conditions shown in [Equation 9] are not satisfied, a triangle is not formed (when either side is 0), or the radius D (k) of the circumscribed circle becomes extremely large, and the frequency with high accuracy This is because the distribution cannot be obtained.

  The radius of the circumscribed circle of N / 3 first triangles, the radius of the circumscribed circle of N / 3 second triangles, and the circumscribed circle of N / 3 third triangles calculated by the above [Equation 6] The N / 3 array D (k) of the second triangle is offset by N / 3 for the N / 3 array D of the second triangle, and the N / 3 array of the third triangle is added to the N / 3 array of the third triangle. Is added with an offset of 2N / 3, and is grouped with a serial number i, the range is reset to i = 0,..., N−1, and the circumscribed circle radius D (i) ( i = 0,..., N-1). And the largest one among the N circumscribed circle radii D (i) of i = 0,..., N−1 is set as the maximum circumscribed circle radius Dmax.

  Next, the frequency distribution calculating means 10 calculates an area ratio that is a ratio of an area between a triangle having the polygon centroid as a vertex and a circumscribed circle of the triangle (step S507). Specifically, by executing the processing according to the following [Equation 10], the areas of the first triangle, the second triangle, and the third triangle in the range of k = 0,..., N / 3-1. The ratio A (k) is calculated.

[Formula 10]
A (k) = D (k) ² / S (k) ^1/2

  As shown in the above [Equation 10], the area ratio A (k) is calculated by dividing the square of the radius D (k) of the circumscribed circle by the square root of the area S (k) of the triangle. . Therefore, the area ratio A (k) is not an accurate area ratio between the triangle and its circumscribed circle. However, it is a value that reflects sharply the shape difference of the triangle from the exact area ratio, the horizontal axis of the frequency distribution is the same distance dimension as the circumscribed circle distribution, it is possible to match the circumscribed circle distribution with the scale Therefore, in the present embodiment, the calculated A (k) is handled as the area ratio. Note that a triangle that does not satisfy even one of the six conditions shown in [Equation 9] is not counted in the frequency distribution of the radius and area ratio of the circumscribed circle.

  The area ratio A (k) of N / 3 first triangles calculated by the above [Equation 10], the area ratio A (k) of N / 3 second triangles, and N / 3 third triangles. For the N / 3 arrays A (k) of the three types of area ratio A (k) of the triangle, an offset of N / 3 is added to the N / 3 array for the second triangle, and the third triangle is After adding an offset of 2N / 3 to the N / 3 array of N, the range of the serial number i is reset to i = 0,..., N−1, and the area ratio A of N triangles A ( i) Obtain (i = 0,..., N−1). And the largest one among N area ratios A (i) of i = 0,..., N−1 is defined as a maximum area ratio Amax.

  Thereafter, the frequency distribution calculating means 10 calculates a circumscribed circle distribution (step S508) which is a frequency distribution of the radius of the circumscribed circle of the triangle, and the frequency of the area ratio which is the ratio of the area of each triangle to the circumscribed circle. An area ratio distribution which is a distribution is calculated (step S509). In the present embodiment, the circumscribed circle distribution and the area ratio distribution are calculated in consideration of the normal vector of the polygon. The reason will be explained.

  FIG. 10 is a diagram illustrating a relationship between a 3D-shaped polygon model and a selected triangle. In FIG. 10, the 3D shape is shown in a two-dimensionally projected state for convenience of explanation. The upper pentagon in FIGS. 10A and 10B is a component A composed of 10 polygons (only 5 polygons are visible on the drawing, but 5 polygons are hidden on the back side). 10A and 10B, the lower hexagon is composed of 12 polygons (only 6 polygons are visible on the drawing, but 6 polygons are hidden on the back side). The component B is shown. FIG. 10 (a) shows a case where a composite part composed of a dodecahedron part and a dodecahedron part is handled as a single unit, and FIG. 10 (b) shows a dodecahedron part and a dodecahedron part respectively. The case of handling as a single unit is shown.

  FIG. 10A shows three triangles composed of points on three polygons, and FIG. 10B shows two triangles composed of points on three polygons. In FIGS. 10A and 10B, the circumscribed circles of these five triangles are indicated by broken lines. As described above, the radii of these circumscribed circles are used to calculate a frequency distribution (circumscribed circle distribution, area ratio distribution) expressing the characteristics of a three-dimensional polygon model.

  When trying to select a triangle composed of points on three polygons as the basis of the frequency distribution, it goes without saying that a single component as shown in FIG. 10B selects a triangle only within each component. On the other hand, in the composite part as shown in FIG. 10A, a triangle is also selected in the component parts, but a triangle is also selected between the component parts. As can be seen by comparing FIG. 10 (a) and FIG. 10 (b), among the triangles selected for the composite part as shown in FIG. 10 (a), there is a component inside each component as shown in FIG. 10 (b). In many cases, the selected triangle is included alone. However, since triangles are selected at random for both the composite part and the component parts, all the triangles selected in each component part of FIG. 10B are not necessarily selected by the composite part of FIG. 10A. It is not included in the triangle. That is, since the frequency distribution of the polygon model of each component part includes the frequency distribution component of the polygon model of each component part, if the polygon model frequency distribution is registered in the database in the form of the composite part, When outputting a 3D shape using multiple polygon models, it is possible to verify whether the frequency distribution of the polygon model for each part partially matches the frequency distribution of the polygon model of the composite part registered in the database. , It is possible to regulate the output of those that match.

  Here, consider a case where congruent triangles are selected by points on three polygons. FIG. 11 is a diagram illustrating a relationship between a 3D-shaped component and a selected triangle when congruent triangles are selected. The polygon model shown in FIG. 11 (a) is slightly different from the polygon model shown in FIG. 10 (a) for convenience of explanation, but the configuration of the polyhedron is the same, and the polygon model shown in FIG. 11 (b) is the same. Similarly, the polygon model shown in FIG. 10B is slightly different in shape but has the same polyhedron configuration. Accordingly, FIG. 11A shows a case where a composite part composed of a dodecahedron part and a dodecahedron part is handled as a single body, and FIG. 11B shows a dodecahedron part and a dodecahedron part. The case where each is handled as a single unit is shown.

  FIG. 11A shows three triangles composed of points on three polygons, and FIG. 11B shows two triangles composed of points on three polygons. The lower two triangles in FIG. 11A are congruent triangles. In this case, the triangles congruent with each other have the same circumscribed circle radius, and therefore the lower two triangles in FIG. 11A do not have a difference in the frequency distribution based on the circumscribed circle radius.

  Therefore, in the present embodiment, the normal vector of the polygon is taken into consideration when creating the circumscribed circle distribution and the area ratio distribution. FIG. 12 is a diagram illustrating a relationship between a positional relationship between a triangle and a polygon and a normal vector of the polygon in the same polygon model as FIG. FIG. 12A shows how a triangle composed of points on three polygons intersects the polygon. In FIG. 12A, a solid line indicates a portion where the triangle is located in front of the polygon, and a broken line indicates a portion where the triangle is located behind the polygon. Comparing the lower two triangles in FIG. 12 (a), it can be seen that they are congruent but differ in positional relationship with the polygon.

  Of the three triangles shown in FIG. 12 (a), the upper and lower triangles are triangles created based on the polygons of the icosahedron component and the dodecahedron component, respectively. Located behind the polygon. However, among the three triangles shown in FIG. 12 (a), the middle triangle is a triangle created based on one polygon in the decahedron and two polygons in the dodecahedron, so the top vertex of the triangle is It will be located in front of the lower polygon in the decahedron.

  In FIG. 12B, the normal vector of the polygon that forms the triangle shown in FIG. 12A and the vector from the center of gravity, which is the point having the average coordinates of the three vertices of the triangle, to each polygon. Is shown. In FIG. 12B, Na1, Na2, Na3, Nb1, Nb2, Nb3, Nb4, and Nb5 are polygon normal vectors, and Ta1, Ta2, Ta3, Tab1, Tab2, Tab3, Tb1, Tb2, and Tb3 are , A vector from the centroid, which is the point having the average coordinates of the three vertices of the triangle, to the centroid, which is the point having the average coordinates of the three vertices of each polygon. The normal vectors and the vectors Na1 and Ta1, Na2 and Ta2, and Na3 and Ta3 from the centroid to the polygons at the three vertices of the triangle formed in the same upper component shown in FIG. Facing the direction. The normal vectors and the vectors Nb2 and Tb1, Nb3 and Tb2, Nb3 and Tb2, Nb4 and Tb3 from the center of gravity to the polygons at the three vertices of the triangle formed in the same lower component shown in FIG. Facing the same direction. However, the normal vectors and the vectors Nb1 and Tab1, Nb1 and Tab2, Nb5 and Tab3 from the center of gravity to the polygons at the three vertices of the triangle formed across the upper and lower components shown in FIG. , There is a gap of about 90 to 180 degrees, and Tab2 faces in the opposite direction. In other words, a triangle that is formed by straddling a plurality of components with a triangle that is configured within the same component has a significant difference in the direction of the normal vector and the vector from the center of gravity to each polygon at each vertex. . By creating a frequency distribution using these vectors, even if there are triangles that are congruent or similar to each other, the difference between whether they are within a component or across components Therefore, it is possible to accurately determine similarity between polygon models.

  Returning to the flowchart of FIG. 7, the frequency distribution calculating means 10 calculates a circumscribed circle distribution that is a frequency distribution of the radius of the circumscribed circle of the triangle (step S508). Specifically, the frequency Hd (md) of the element md is calculated for i = 0,..., N−1 by executing processing according to the following [Equation 11].

[Formula 11]
If Dmax · md / MD ≦ D (i) <Dmax · (md + 1) / MD,
Hd (md) ← Hd (md) + SQ, SQsum ← SQsum + SQ
SQ = [Sp (G1 (i)). {Ex (G2 (i), G3 (i), G1 (i)). Xn (G1 (i)) + Ey (G2 (i), G3 (i), G1) (I)). Yn (G1 (i)) + Ez (G2 (i), G3 (i), G1 (i)). Zn (G1 (i))} + Sp (G2 (i)). {Ex (G3 (I), G1 (i), G2 (i)). Xn (G2 (i)) + Ey (G3 (i), G1 (i), G2 (i)). Yn (G2 (i)) + Ez (G3 (I), G1 (i), G2 (i)). Zn (G2 (i))} + Sp (G3 (i)). {Ex (G1 (i), G2 (i), G3 (i)) .. Xn (G3 (i)) + Ey (G1 (i), G2 (i), G3 (i)) Yn (G3 (i)) + Ez (G1 (i), G2 (i), G3 (i)) Zn (G3 (i))}] / 3
However, in the case of 0 ≦ i ≦ N / 3-1, as q = R1 (i), G1 (i) = G1 (R1 (i)), G2 (i) = G2 (R2 (i)), G3 ( i) = G3 (R3 (i))
In the case of N / 3 ≦ i ≦ 2N / 3-1, as q = R2 (i), G1 (i) = G1 (R2 (i)), G2 (i) = G2 (R3 (i)), G3 ( i) = G3 (R1 (i))
In the case of 2N / 3 ≦ i ≦ N−1, q = R3 (i) and G1 (i) = G1 (R3 (i)), G2 (i) = G2 (R1 (i)), G3 (i) = G3 (R2 (i)).

  In the above [Expression 11], SQ is the area of each polygon in the inner product value of vectors (Ex (), Ey (), Ez ()) from the centroid of the triangle to each vertex and the normal vector Xn () of each polygon. It is a weight value multiplied by Sp (). The vectors (Ex (), Ey (), Ez ()) from the centroid of the triangle to the vertices are unit vectors from the centroid of the triangle to the vertices calculated using the above [Equation 3] and [Equation 4]. Is calculated using [Equation 11] indicates that the circumscribed circle radius D (i) of the triangle is equal to or greater than the value obtained by multiplying the maximum circumscribed circle radius Dmax by md / MD and smaller than the value obtained by multiplying (md + 1) / MD. This means that a weight value SQ based on three polygons having vertices as polygon centroids is added to Hd (md). Similarly, the weight value SQ is added to the weight sum value SQsum. The weight value SQ becomes a small value when the direction from the center of gravity of the triangle to each vertex is different from the normal vector direction of each polygon, and may take a negative value when the direction is further reversed. If it does so, the value added to frequency Hd (md) will become small or will be subtracted. Such a phenomenon is likely to occur when the three polygons constituting the triangle belong to the polygon models of different parts, and as a result, the three polygons constituting the triangle belong to the polygon model of the same part with the frequency Hd ( It tends to be counted in md). That is, the features that cross a plurality of parts are suppressed in the frequency distribution, and the characteristics of the individual parts are likely to remain.

  The circumscribed circle distribution Hd (md) (md = 0,..., MD-1) is calculated by executing the processing according to the above [Equation 11] for N triangles. Since each element is not simply a frequency, but a weight value obtained by multiplying the inner product value of the vector from the center of gravity of the triangle to each vertex and the normal vector of each polygon by the area of the polygon is added, the circumscribed circle distribution Hd (Md) represents a circumscribed circle distribution weighted by weight. When simply adding 1 instead of area, or simply adding the area of a polygon, the features that straddle multiple parts remain in the polygon model composed of multiple parts, and the characteristics of the individual parts are buried. End up. Therefore, in this embodiment, the weight value SQ is added when the circumscribed circle distribution is calculated. However, if the target polygon model is composed of a single part, it is possible to maintain a certain degree of collation accuracy even when adding 1 or simply adding the area of the polygon. Since the normal vector is not taken into account, it is impossible to identify the difference whether or not the polygon model includes a cavity.

  Eventually, by executing the processing according to [Formula 11], the frequency distribution calculating means 10 prepares a one-dimensional array composed of elements of a predetermined number MD, and calculates the maximum radius of the circumscribed circle calculated. The range normalized by the value (maximum circumscribed circle radius Dmax) is divided equally into a predetermined number MD, and the radius D (i) of each circumscribed circle is set to any one of the predetermined number MD based on the value. Assigned to the element md, the number corresponding to the element md is obtained, and the inner product value of the unit vector from the center of gravity of the triangle formed by a predetermined point of the three polygons to each vertex and the normal vector of the polygon including the vertex The circumscribed circle distribution is calculated by calculating an average value of values obtained by multiplying the area of the polygon as a weight value and performing weighting.

  Next, the frequency distribution calculating means 10 calculates an area ratio distribution that is a frequency distribution of an area ratio that is a ratio of the area between each triangle and its circumscribed circle (step S509). Specifically, the frequency Ha (ma) of the element ma is calculated for i = 0,..., N−1 by executing processing according to the following [Equation 12].

[Formula 12]
If Dmax ² · ma / MA ≦ A (i) <Dmax ² · (ma + 1) / MA,
Ha (ma) ← Ha (ma) + SQ
If A (i) ≧ Dmax ² , Ha (MA-1) ← Ha (MA-1) + SQ

The weight value SQ obtained by multiplying the inner product value of the vector from the center of gravity of the triangle to each vertex and the normal vector of each polygon in [Equation 12] by the area of the polygon is also obtained by the processing according to [Equation 11]. Use the calculated value. The above [Equation 12] is obtained when the area ratio A (i) is equal to or larger than the value obtained by multiplying the square of the maximum circumscribed circle radius Dmax ² by ma / MA and smaller than (ma + 1) / MA. This means that the weight value SQ using three polygons having vertices as centroids is added to Ha (ma).

  Eventually, by executing the processing according to the above [Equation 12], the frequency distribution calculating means 10 prepares a one-dimensional array composed of elements of a predetermined number MA, and calculates the maximum radius of the circumscribed circle calculated. A range normalized by a value obtained by squaring a value (maximum circumscribed circle radius Dmax) is equally divided into a predetermined number MA, and each area ratio A (i) is set to any one of the predetermined number MA based on the value. The area ratio distribution is calculated by assigning to the element ma and counting the number corresponding to the element ma.

Since the circumscribed circle radius and area ratio depend on the scale of the polygon model, if the distribution is created by normalizing the horizontal axis to the range of the maximum value, a distribution that does not depend on the scale can be obtained. At this time, if a distribution normalized by the maximum value independent of the circumscribed circle radius and the area ratio is created, a distribution that does not depend on the scale between the circumscribed circle radius and the area ratio can be obtained, and the robustness to shape deformation is increased. On the other hand, shape discrimination becomes weak. In the present invention, since the distribution is normalized by the maximum value defined using the maximum circumscribed circle radius, which is the same reference value as the circumscribed circle radius, the maximum value is obtained for the circumscribed circle radius and the area ratio. Although the distribution is different, the distribution maintains the scale ratio between the two, and the spread of the distribution is narrower and sharper than when normalized with independent maximum values of the circumscribed circle radius and area ratio, and the shape discrimination Becomes higher. Actually, since the area ratio takes a value equal to or larger than the square of the maximum value of the circumscribed circle radius (maximum circumscribed circle radius), the area ratio is normalized so as to be saturated in the range of the square of the maximum value. In the present embodiment, as shown in the last line of [Expression 12] above, when Dmax ² that is the square of the maximum circumscribed circle radius Dmax is exceeded, the element corresponding to the maximum value is counted. With this setting, in the case of a sphere, the area ratio distribution has a peak at the maximum value, and has almost the same form as the circumscribed circle distribution. However, as the shape deviates from the sphere, the difference between the area ratio distribution and the circumscribed circle distribution increases. The range of normalization can be set as appropriate, but is preferably 3/2 to the third power of the maximum value of the circumscribed circle radius. If the ratio is less than 3/2, the ratio of the area ratio exceeding the maximum value of the element ma (scale) (3/2 of the maximum value of the circumscribed circle radius) increases, and the distribution is concentrated on the maximum value of the element ma. Therefore, the shape is not accurately reflected. Further, when it exceeds the third power, a distribution in which the blank on the maximum value side of the element ma is large is formed.

  The area ratio distribution Ha (ma) (ma = 0,..., MA−1) is calculated by executing the processing according to the above [Equation 12] for N triangles. Since each element is not simply a frequency, but a weight value obtained by multiplying the inner product value of the vector from the center of gravity of the triangle to each vertex and the normal vector of each polygon by the area of the polygon is added, the area ratio distribution Ha (Ma) indicates a weight value weighted area ratio distribution. When simply adding 1 instead of area, or simply adding the area of a polygon, the features that straddle multiple parts remain in the polygon model composed of multiple parts, and the characteristics of the individual parts are buried. End up. Therefore, in this embodiment, the weight value SQ is added when calculating the area ratio distribution. However, if the target polygon model is composed of a single part, it is possible to maintain a certain degree of collation accuracy even when adding 1 or simply adding the area of the polygon. Since the normal vector is not taken into account, it is impossible to identify the difference whether or not the polygon model includes a cavity.

Eventually, by executing the processing according to the above [Equation 12], the frequency distribution calculating means 10 prepares a one-dimensional array composed of elements of a predetermined number MA, and calculates the maximum radius of the circumscribed circle calculated. The range normalized by the square of the value (Dmax ² ) is equally divided into a predetermined number MA, and each area ratio A (i) is set to any element ma of the predetermined number MA based on the value. To obtain the number corresponding to the element ma, and calculate the inner product value of the unit vector from the center of gravity of the triangle formed by the predetermined points of the three polygons to each vertex and the normal vector of the polygon including the vertex. An average value of values obtained by multiplying the area of the polygon is calculated as a weight value, and weighting is performed to calculate the area ratio distribution.

  Once the circumscribed circle distribution and the area ratio distribution are calculated, it is next determined whether or not the loop counter LC is equal to or greater than a specified value (step S510). As a result of the determination, if the loop counter LC is less than the specified value, a process of shifting the arrangement of the two groups by 1 is performed (step S511). For example, when the order of the first group is fixed, in the present embodiment, the random number array R2 (k used for the two groups, the second group and the third group, is executed by executing the processing according to the following [Formula 13]. ), The order of the random number array R3 (k) is shifted.

[Formula 13]
Ro = R2 (0), Ro3 = R3 (0),
For k = 0, ..., N / 3-2,
R2 (k) ← R2 (k + 1), R3 (k) ← R3 (k + 1) are repeated,
It is assumed that R2 (N / 3-1) = Ro and R3 (N / 3-1) = Ro3.

  When the order of the second group is fixed or when the order of the third group is fixed, the relationship between the groups is changed and the process according to [Equation 13] is executed. In addition, a process of incrementing the loop counter LC (LC ← LC + 1) is also performed. When there is a frequency distribution that has already been calculated, the frequency value corresponding to each element is added to each element of the frequency distribution. In step S511, after shifting the arrangement of the two groups, the combination of the polygons of the two groups and the other group is changed from the first time, and the processing of steps S505 to S509 is executed, and the circumscribed circle distribution and area are changed. Calculate the ratio distribution. The calculation process of circumscribed circle distribution and area ratio distribution in step S505 to step S509 is repeated a predetermined number of times set as a specified value. The specified value can be set as appropriate, but is about 10 when the total number of polygons N = 10000.

  That is, every time the circumscribed circle distribution and the area ratio distribution are calculated once, the process of calculating the circumscribed circle distribution and the area ratio distribution again by changing the order of the polygons in two of the three groups is repeatedly performed. It will be. When the loop counter LC reaches the specified value, it is determined in step S510 that the loop counter LC is equal to or greater than the specified value, so that the two frequency distributions are normalized (step S512).

  Specifically, by multiplying Hd (md) calculated by the above [Equation 11] by 100 / {SQsum × LC} and replacing it with Hd (md), the unit is normalized to the rate [%]. Yes. That is, the value Hd (md) of each element is divided by the multiplication value of the weight sum value SQsum, which is the sum value of the weight values SQ, and the loop count LC. Since the weight value SQ is obtained by using the area of the polygon, even if the polygon model has a different total area area, that is, a polygon model with a different scale, it is converted to a circumscribed circle distribution of the same scale, Judgment is possible as a model. In addition, since it is divided by the loop number LC, an average value for the loop number is obtained. Since Hd (md) has a frequency distribution, it needs to be a value of 0 or more. However, since the weight value SQ calculated by [Equation 11] can take a negative value, the obtained Hd (md) may be a negative value. In this case, an absolute value (that is, − 1), and Hd (md) is changed to a value of 0 or more.

  Further, the unit is normalized to the rate [%] by multiplying Ha (ma) calculated by the above [Equation 12] by 100 / {SQsum × LC} and replacing it with Ha (ma). That is, the value Ha (ma) of each element is divided by the multiplication value of the weight sum value SQsum, which is the sum value of the weight values SQ, and the loop count LC. Since the weight value SQ is obtained by using the area of the polygon, even if the polygon models have different total area values, that is, polygon models with different scales, they are converted to the same scale area ratio distribution, Judgment is possible as a model. In addition, since it is divided by the loop number LC, an average value for the loop number is obtained. Since Ha (ma) has a frequency distribution, it needs to be a value of 0 or more. However, since the weight value SQ calculated by [Equation 11] can take a negative value, Ha (ma) obtained by [Equation 12] may be a negative value. (Ie, multiply by -1), and change Ha (ma) to a value of 0 or more.

  After normalization of the two kinds of frequency distributions, next, the actual size maximum circumscribed circle radius is calculated (step S513). Specifically, the actual size maximum circumscribed circle radius Wmax is calculated by executing processing according to the following [Equation 14].

[Formula 14]
Wmax = Dmax · Sout

  In the above [Equation 14], Dmax is the maximum circumscribed circle radius, and Sout is output scale information. The actual maximum circumscribed circle radius Wmax is obtained by multiplying the maximum circumscribed circle radius Dmax by the output scale information Sout.

  In the present embodiment, when calculating the radius of the circumscribed circle of the triangle and the area ratio of the triangle, a triangle having the three centroids of the three polygons as the three vertices is created. The vertices of the triangles are preferably centroids having the average coordinates of the vertices of the polygons, but can also be triangles connecting predetermined points on the polygons other than the centroids. The predetermined points on the polygon include, for example, any vertex constituting the polygon, a point having a value that is exactly halfway between the maximum value and the minimum value of each vertex of the polygon, and the polygon is a triangle. In some cases, inner, outer, vertical, side, etc. can be used.

<3.3.2. Second method>
Next, the second method will be described. FIG. 13 is a flowchart showing details of the frequency distribution calculation processing by the second method. The same processes as those in the first method are denoted by the same reference numerals and description thereof is omitted. Also in the second method, steps S501 to S509 are performed in the same manner as in the first method. Then, as in step S512 of the first method, normalization of the two types of frequency distribution is performed (step S512). In the second method, normalization is forcibly performed after the calculation of the two types of frequency distributions. Specifically, the unit is normalized to the rate [%] by multiplying Hd (md) calculated by the above [Equation 11] by 100 / SQsum and replacing it with Hd (md). Further, the unit is normalized to the rate [%] by multiplying Ha (ma) calculated by the above [Equation 12] by 100 / SQsum and replacing it with Ha (ma). Unlike the first method, division by the loop counter LC is not performed.

  If normalization of the circumscribed circle distribution and the area ratio distribution is performed, it is next determined whether or not the loop counter LC is 1 or more (step S521). This determines whether or not the frequency distribution is calculated for the first time. When the loop counter LC is less than 1, it means that the frequency distribution is calculated for the first time, so that the process of shifting the arrangement of the two groups by 1 is performed (step S511). Specifically, similarly to step S511 of the first method, by executing the process according to [Formula 13], two of the arrays R1 (k), R2 (k), and R3 (k) The order of the array is shifted.

  In step S511, after shifting the arrangement of the two groups, the combination of the polygons of the two groups and the other group is changed from the first time, and the processes of steps S505 to S509, S512, and S521 are executed. Normalize the circle distribution and area ratio distribution. That is, every time the circumscribed circle distribution and the area ratio distribution are calculated once, the process of calculating the circumscribed circle distribution and the area ratio distribution again by changing the order of the polygons in two of the three groups is repeatedly performed. . In the second and subsequent times, in step S521, since the loop counter LC is determined to be 1 or more, the immediately preceding circumscribed circle distribution and area ratio distribution are compared (step S522). First, the processing according to the following [Equation 15] is executed to calculate the Euclidean distance DD between the calculated circumscribed circle distribution and the immediately preceding circumscribed circle distribution. The Euclidean distance is a distance in the Euclidean space given as a value obtained by squaring the absolute value of the difference between the frequencies of each element. The Euclidean distance DD is obtained as a distance between two points in the MD dimensional Euclidean space.

[Formula 15]
DD = Σ _{md = 0, MD-1} [{Hd (md) −Hdp (md)} ² / MD] ^1/2

In the above [Formula 15], the subscript “md = 0, MD-1” of Σ is the following [...] ^1/2 when md takes all integers from 0 to MD-1. The sum is calculated. Hdp (md) represents the circumscribed circle distribution just before.

  Subsequently, by executing processing according to the following [Equation 16], the Euclidean distance DA between the calculated area ratio distribution and the immediately preceding area ratio distribution is calculated. The Euclidean distance DA is obtained as a distance between two points in the MA dimensional Euclidean space.

[Formula 16]
DA = Σ _{ma = 0, MA-1} [{Ha (ma) −Hap (ma)} ² / MA] ^1/2

In the above [Expression 16], the subscript “ma = 0, MA-1” of Σ is the following [...] ^1/2 when ma takes all integers from 0 to MA-1. The sum is calculated. Hap (ma) indicates the immediately preceding area ratio distribution.

  Next, the frequency distribution calculation unit 10 compares the Euclidean distance of the circumscribed circle distribution and the area ratio distribution calculated in step S522 with the respective determination threshold values (step S523). Specifically, when both of the Euclidean distances DD and DA are smaller than the determination threshold value, the saturated state is determined. When either one of the Euclidean distances DD and DA is equal to or greater than the determination threshold value, the generation is in progress. judge. The determination threshold can be arbitrarily set, but here it is set to 0.05.

  When it is determined in step S523 that the state is saturated, that is, when similarity is recognized between the two, the frequency distribution calculating unit 10 officially converts the circumscribed circle distribution and the area ratio distribution calculated last into two types of frequencies. The distribution is determined (step S524). That is, the circumscribed circle distribution and area ratio distribution immediately after the calculation are compared with the circumscribed circle distribution and area ratio distribution obtained immediately before the circumscribed circle distribution and area ratio distribution obtained immediately before the calculation. The area ratio distribution is a circumscribed circle distribution and an area ratio distribution to be verified. At this time, since Hd (md) has a frequency distribution, it needs to be a value of 0 or more. Therefore, when the obtained Hd (md) is a negative value, the absolute value is taken (that is, multiplied by -1), and Hd (md) is changed to a value of 0 or more. Further, since Ha (ma) has a frequency distribution, it needs to be a value of 0 or more. Therefore, when the obtained Ha (ma) is a negative value, the absolute value is taken (that is, multiplied by -1), and Ha (ma) is changed to a value of 0 or more.

  If it is determined in step S523 that the group is in the process of generation, a process for shifting the arrangement of the two groups by 1 is performed (step S511), and then the processes in steps S505 to S509, S512, S521, and S522 are repeatedly executed.

  When the two types of frequency distributions are determined, the actual size maximum circumscribed circle radius is calculated by executing the processing according to [Formula 14] as in the first method (step S513).

  FIG. 14 shows a triangle for obtaining the circumscribed circle distribution and the area ratio distribution obtained from the target model and the circumscribed circle. FIG. 14 shows a polygon model when the polygon is triangular. For three polygons selected from the polygon model, a triangle is created by connecting the centroids having the average coordinates of the vertices of each polygon. Then, a circumscribed circle of a triangle is obtained. FIG. 14 shows the relationship between the triangle and its circumscribed circle and radius. In FIG. 14, the downward arrow indicates the radius of the circumscribed circle.

In general, when the polygon model has a shape close to a sphere, the circumscribed circle of a triangle connecting the centers of three randomly selected polygons is a circle when the sphere is cut by a plane formed by the three centers. Become. That is, in the case of a sphere, the circumscribed circle radius often coincides with the radius of the sphere, and in the circumscribed circle distribution, a peak appears at one location corresponding to the radius of the sphere. However, as the polygon density gets closer to the polyhedron, the circumscribed circle distribution spreads toward the shorter circumscribed circle radius, and the circumscribed circle distribution becomes more complex as the polygon model deviates from the sphere. Therefore, the circumscribed circle distribution using the circumscribed circle radius is extremely effective for identifying the 3D shape. On the other hand, when the polygon model is a sphere, most of the values exceed the square of the maximum circumscribed circle radius set to the maximum value, and the area ratio distribution has a peak at the maximum value. The shape is almost the same as the circumscribed circle distribution, but as the polygon model deviates from the sphere, the value that exceeds the square of the maximum circumscribed circle radius decreases, the area ratio distribution shifts to the 0 side, and the circumscribed circle distribution. Equipped with shape discrimination that is equivalent to or better than However, since it has a complicated form different from the circumscribed circle distribution except for the sphere, it has a function to supplement the circumscribed circle distribution. In the present invention, since the maximum value of the area ratio distribution is set to a value depending on the maximum circumscribed circle radius, the scale on the horizontal axis of the circumscribed circle distribution and the area ratio distribution is automatically maintained at a predetermined ratio.

<3.4. Frequency distribution matching processing>
Next, the frequency distribution matching process in step S130 will be described. First, the frequency distribution matching unit 20 calculates the maximum actual size of the frequency distribution registered in the record re (re = 0,..., RE−1) from the RE records stored in the restriction model database 60. Extract the circumscribed circle radius. The actual size maximum circumscribed circle radius of the record re is expressed by Wmaxo (re). Then, the frequency distribution matching unit 20 executes processing according to the following [Equation 17] to match the circumscribed circle distribution Hd (md) calculated from the target model.

[Formula 17]
MD ′ = MD · Wmax / Wmaxo (re)
MD1 = md · Wmax / Wmaxo (re)
MD2 = (md + 1) · Wmax / Wmaxo (re) −1
When md ≦ MD ′, Hd ′ (md) = Σ _{md = MD1, MD2} Hd (md)
When MD ′ <md <MD, Hd ′ (md) = 0

  As a result of executing the process according to the above [Equation 17], a circumscribed circle distribution Hd ′ (md) subjected to the matching process is obtained. Subsequently, the frequency distribution matching unit 20 executes processing according to the following [Equation 18], thereby matching the area ratio distribution Ha (ma) calculated from the target model.

[Formula 18]
MA ′ = MA · Wmax / Wmaxo (re)
MA1 = ma · Wmax / Wmaxo (re)
MA2 = (ma + 1) · Wmax / Wmaxo (re) −1
When ma ≦ MA ′, Ha ′ (ma) = Σ _{md = MA1, MA2} Ha (ma)
If MA ′ <ma <MA, Ha ′ (ma) = 0

  As a result of executing the processing according to the above [Equation 18], the matched area ratio distribution Ha ′ (ma) is obtained.

<3.5. Frequency distribution enhancement processing>
Next, the frequency distribution enhancement processing in step S170 will be described. This emphasis process is particularly effective when the target model represents a part of a product and the frequency distribution of the entire product is registered in the regulation model database 60. First, the frequency distribution enhancement means 30 performs enhancement processing on the frequency distribution of the matched target model and the frequency distribution stored in the restriction model database 60. Specifically, the frequency distribution enhancement means 30 first prepares enhancement components (window functions) W (md) and W (ma) defined by the following [Equation 20].

[Formula 20]
W (md) = 1 / (md + 1) ²
md = 0,..., MD-1
W (ma) = 1 / (ma + 1) ²
ma = 0,..., MA-1

  Both W (md) and W (ma) can take values of 0 <W (md) and W (ma) ≦ 1. Subsequently, the frequency distribution emphasizing means 30 uses the frequency distribution registered in the record re (re = 0,..., RE−1) among the RE records stored in the restriction model database 60 as a frequency distribution. A circumscribed circle distribution Hdo (re, md) (md = 0,..., MD-1) and an area ratio distribution Hao (re, ma) (ma = 0,..., MA-1) are extracted. Then, by executing the processing according to the following [Formula 21], the circumscribed circle distribution Hd ′ (md) of the matched target model and the circumscribed circle distribution Hdo of each record re stored in the restriction model database 60 For (re, md), enhancement processing is performed so that all values in the range of md = 0,..., MD−1 are updated.

[Formula 21]
Hd ″ (md) = Hd ′ (md) · W (md)
Hdo ′ (re, md) = Hdo (re, md) · W (md)

  In the above [Formula 21], the circumscribed circle distribution Hd ′ (md) of the matched target model and the circumscribed circle distribution Hdo (re, md) of each record re stored in the regulation model database 60 are as follows. Processing for multiplying all values in the range of md = 0,..., MD-1 by the emphasis component W (md) is performed. The enhancement component W (md) plays a role as a so-called window function that extracts only a specific section of data, and the above [Equation 21] performs a process of multiplying the window function. As a result of executing the process according to the above [Equation 21], the circumscribed circle distribution Hd ″ (md) of the target model subjected to the emphasis process and the circumscribed circle distribution Hdo ′ (re, md) of each of the emphasized regulation models are obtained. Obtained as an emphasis frequency distribution. Subsequently, the frequency distribution emphasizing means 30 stores the area ratio distribution Ha ′ (ma) of the matched target model in the regulated model database 60 by executing processing according to the following [Equation 22]. Emphasis processing is performed so that all values in the range of ma = 0,..., MA−1 are updated with respect to the area ratio distribution Hao (re, ma) of each record re.

[Formula 22]
Ha ″ (ma) = Ha ′ (ma) · W (ma)
Hao '(re, ma) = Hao (re, ma) · W (ma)

  In the above [Equation 22], the area ratio distribution Ha ′ (ma) of the normalized target model and the area ratio distribution Hao (re, ma) of each record re stored in the restriction model database 60 are respectively calculated. , Ma = 0,..., MA-1 are multiplied by the emphasis component W (ma). The emphasis component W (ma) plays a role as a so-called window function that extracts only a specific section of data, and the above [Equation 22] performs processing for multiplying the window function as in [Equation 21]. Will be. As a result of executing the processing according to the above [Equation 22], the area ratio distribution Ha ″ (ma) of the target model subjected to the emphasis process and the area ratio distribution Hao ′ (re, ma) of each emphasizing regulation model are obtained. Obtained as an emphasis frequency distribution.

FIG. 15 is a diagram illustrating a change in the frequency distribution by the frequency distribution enhancement processing in step S170. 15 (a), (b), (d), and (e) show the frequency distribution, the horizontal axis shows the element md or ma, and the vertical axis shows the frequency Hd (md) or Ha (ma). . FIG. 15C shows a window function W (m) = 1 / (m + 1) ² that is an enhancement component (m is a generalization of md or ma).

  In the example of FIG. 15, the regulation model corresponding to FIG. 15A represents an entire product, and the target model corresponding to FIG. 15B represents a part of a product. Show. For this reason, the regulation model in which the radius of the circumscribed circle tends to be larger than that of only the part has a distribution over the entire horizontal axis having the maximum circumscribed circle radius as the maximum value, as shown in FIG. As shown in FIG. 15 (b), the target model that exists but tends to have a smaller radius of the circumscribed circle compared to the entire product is a short-range region on the horizontal axis with the maximum circumscribed circle radius as the maximum value. The distribution exists only in the (low range), that is, the left part of the drawing.

  As shown in FIG. 15C, the emphasis component used in the present embodiment is a window function whose value increases as the value of the element m decreases. Therefore, only the short distance area is easily emphasized. For this reason, when the emphasis process is performed, the frequency distribution of the regulatory model that represents the entire product is emphasized only in the short-range area, and the correlation is likely to increase when collation with the target model after the emphasis process is performed. .

<3.6. Frequency distribution matching process>
Next, the frequency distribution matching process in step S200 will be described. FIG. 16 is a flowchart showing the frequency distribution matching process. First, the frequency distribution matching unit 40 acquires a frequency distribution (emphasized frequency distribution) extracted from the restriction model database 60 and subjected to an emphasis process (step S610). As the frequency distribution subjected to enhancement processing, circumscribed circle distribution Hdo ′ (re, md) (md = 0,..., MD−1), area ratio distribution Hao ′ (re, ma) (ma = 0,. , MA-1). In the frequency distribution matching processing in step S200, the enhancement frequency distributions Hd ″ (md) and Hdo ′ (re, md) calculated in the above [Formula 21] and [Formula 22] are described for the sake of simplicity. , Ha ″ (ma) and Hao ′ (re, ma) are treated as Hd (md), Hdo (re, md), Ha (ma), and Hao (re, ma), respectively.

  Next, the frequency distribution matching unit 40 calculates a correlation coefficient between each element between the circumscribed circle distribution of the emphasized target model and the circumscribed circle distribution of the regulated model extracted from the regulated model database 60 and enhanced. Calculate (step S620). The frequency distribution matching means 40 executes the process according to the following [Equation 23], whereby the average value Ad of the circumscribed circle distribution Hd (md) of the target model subjected to the emphasis process, the circumscribing of the emphasizing regulation model. An average value Ado (re) of the circle distribution Hdo (re, md) is calculated.

[Formula 23]
Ad = Σ _{md = 0, MD-1} Hd (md) / MD
Ado (re) = Σ _{md = 0, MD-1} Hdo (re, md) / MD

  Subsequently, by executing processing according to the following [Equation 24], the standard deviation Sd of the circumscribed circle distribution Hd (md) of the target model and the standard deviation Sdo of the circumscribed circle distribution Hdo (re, md) of the regulated model (Re) is calculated.

[Formula 24]
Sd = [Σ _{md = 0, MD-1} (Hd (md) −Ad) ² ] ^1/2
Sdo (re) = [Σ _{md = 0, MD-1} (Hdo (re, md) −Ado (re)) ² ] ^1/2

  Strictly speaking, the standard deviation needs to be further divided by a constant MD within {} in the above [Equation 24]. However, since the purpose here is to calculate the correlation coefficient, it is necessary to divide by the constant MD in the term for calculating the covariance of the numerator in [Equation 25] to be described later. The operation of dividing by the constant MD is canceled (the denominator is divided twice by the square root of the constant MD).

  Next, using the calculated average value and standard deviation, a process according to the following [Equation 25] is executed, whereby the circumscribed circle distribution of the target model and the circumscribed circle distribution of the restriction model corresponding to the record re A correlation coefficient Dd (re) is calculated.

[Formula 25]
Dd (re) = [Σ _{md = 0, MD-1} (Hd (md) −Ad) · (Hdo (re, md) −Ado (re))] / (Sdo (re) · Sd)

  In the above [Equation 25], the subscript “md = 0, MD-1” of Σ indicates that the sum is obtained when md takes all integers from 0 to MD-1. The correlation coefficient Dd (re) is obtained by dividing the covariance of the frequency distributions Hd (md) and Hdo (re, md) by their standard deviations. In general, the processing load is high when dividing the square root of the denominator twice as in the calculation of [Equation 25]. For this reason, in the field of image processing, what is required only by the product-sum operation of numerators is called “correlation coefficient”, and Dd (re) shown in the above [Equation 25] is called “normalized correlation coefficient”. There are also customs.

  Next, the frequency distribution matching unit 40 compares the correlation coefficient Dd (re) of the circumscribed circle distribution calculated in step S620 with the determination threshold value (step S630). When the correlation coefficient Dd (re) is greater than or equal to the determination threshold value, it is determined as conforming, and when the correlation coefficient Dd (re) is smaller than the determination threshold value, it is determined as non-conforming. The determination threshold value can be arbitrarily set as long as it is a positive value. Here, the correlation coefficient value taking a range of +20.0 (−1 to +1) is multiplied by 100 and expressed in% dimension. ).

  If it is determined in step S630 that the data is suitable, the frequency distribution matching unit 40 calculates a correlation coefficient between the elements based on the area ratio distribution of the target model and the area ratio distribution of the restriction model (step S640). First, by executing processing according to the following [Equation 26], the average value Aa of the area ratio distribution Ha (ma) of the target model, and the average value Aao () of the area ratio distribution Hao (re, ma) of the regulated model re) is calculated.

[Formula 26]
Aa = Σ _{ma = 0, MA-1} Ha (ma) / MA
Aao (re) = Σ _{ma = 0, MA-1} Hao (re, ma) / MA

  Subsequently, by executing processing according to the following [Equation 27], the standard deviation Sa of the area ratio distribution Ha (ma) of the target model and the standard deviation Sao of the area ratio distribution Hao (re, ma) of the regulated model (Re) is calculated.

[Formula 27]
Sa = [ _{Σma = 0, MA-1} (Ha (ma) −Aa) ² ] ^1/2
Sao (re) = [Σma _{= 0, MA-1} (Hao (re, ma) −Aao (re)) ² ] ^1/2

  Strictly speaking, the standard deviation needs to be further divided by a constant MA within {} in the above [Equation 27]. However, since the purpose here is to calculate the correlation coefficient, it is necessary to divide by the constant MA in the term for calculating the covariance of the numerator in [Equation 28], which will be described later. The operation of dividing by the constant MA is canceled (the denominator is divided by the square root of the constant MA twice).

  Next, by using the calculated average value and standard deviation, the processing according to the following [Equation 28] is executed, whereby the area ratio distribution of the target model and the area ratio distribution of the regulation model corresponding to the record re A correlation coefficient Da (re) is calculated.

[Formula 28]
Da (re) = [Σma _{= 0, MA-1} (Ha (ma) -Aa). (Hao (re, ma) -Aao (re))] / (Sao (re) .Sa)

  In the above [Equation 28], the subscript “ma = 0, MA−1” of Σ indicates that the sum is obtained when ma takes all integers from 0 to MA−1. The correlation coefficient Da (re) is obtained by dividing the covariance of the frequency distributions Ha (ma) and Hao (re, ma) by the respective standard deviations. In general, the processing load is high when dividing the square root of the denominator twice as in the calculation of [Equation 28]. For this reason, in the field of image processing, what is required only by the product-sum operation of numerators is called “correlation coefficient”, and Da (re) shown in the above [Equation 28] is called “normalized correlation coefficient”. There are also customs.

  Next, the frequency distribution matching unit 40 compares the correlation coefficient Da (re) of the area ratio distribution calculated in step S640 with the determination threshold value (step S650). If the correlation coefficient Da (re) is greater than or equal to the determination threshold value, it is determined as conforming, and if the correlation coefficient Da (re) is smaller than the determination threshold value, it is determined as non-conforming. The determination threshold value can be arbitrarily set as long as it is a positive value. Here, the correlation coefficient value taking a range of +20.0 (−1 to +1) is multiplied by 100 and expressed in% dimension. ).

  When it is determined in step S650 that the data match, the frequency distribution matching unit 40 determines that the circumscribed circle distribution of the target model subjected to the enhancement process and the circumscribed circle distributions of the regulated model extracted from the regulation model database 60 and enhanced. To calculate the peak position correlation (step S660). The peak position correlation indicates a correlation between peak positions that are positions where the frequency is highest in the frequency distribution. The frequency distribution matching means 40 executes processing according to the following [Equation 29], thereby performing circumscribed circle distribution Hd (md) of the emphasized target model and circumscribed circle distribution Hdo ( The peak position correlation Pd (re) of (re, md) is calculated.

[Formula 29]
Pd (re) = {MD / 4- | mdM-mdoM (re) |} .400 / MD

  In the above [Equation 29], mdM is the value of md when Hd (md) is maximum, and mdoM (re) is the value of md when Hdo (re, md) is maximum, that is, the peak position. is there. Moreover, | mdM−mdoM (re) | is a peak position difference indicating a difference between peak positions. When mdM and mdoM (re) match, the peak position difference | mdM−mdoM (re) | = 0 and the peak position correlation Pd (re) = 100, and when mdM and mdoM (re) are farthest, theoretically Since the peak position difference | mdM−mdoM (re) | = MD−1 and the peak position correlation Pd (re) is approximately −300, the peak position correlation Pd (re) is theoretically −300 <Pd ( re) takes a value of ≦ 100. However, since it is rare that the peak position difference | mdM−mdoM (re) | exceeds MD / 2 based on experience, the peak position correlation Pd (re) is usually −100 <Pd (re) ≦ 100. Takes a value. The peak position correlation Pd (re) is a value that increases as the peak position difference | mdM−mdoM (re) | decreases, and is determined based on the peak position difference.

  Next, the frequency distribution matching unit 40 compares the peak position correlation Pd (re) of the circumscribed circle calculated in step S660 with the determination threshold value (step S670). If the peak position correlation Pd (re) is greater than or equal to the determination threshold value, it is determined to be suitable, and if the peak position correlation Pd (re) is smaller than the determination threshold value, it is determined to be non-conforming. The determination threshold can be arbitrarily set as long as it is a positive value, but here it is +50.0.

  If it is determined in step S670 that the data match, the frequency distribution matching unit 40 compares the area ratio distribution of the emphasized target model and the area ratio distribution of the restriction model extracted from the restriction model database 60 and emphasized. To calculate the peak position correlation (step S680). The frequency distribution matching means 40 executes the processing according to the following [Equation 30], whereby the area ratio distribution Ha (ma) of the emphasized target model and the area ratio distribution Hao ( The peak position correlation Pa (re) of re, ma) is calculated.

[Formula 30]
Pa (re) = {MA / 4- | maM-maoM (re) |} .400 / MA

  In the above [Equation 30], maM is the value of ma when Ha (ma) is maximum, and maoM (re) is the value of ma when Hao (re, ma) is maximum, that is, the peak position. is there. Further, | maM−maoM (re) | is a peak position difference indicating a difference between peak positions. When maM and maoM (re) match, the peak position difference | maM−maoM (re) | = 0 and the peak position correlation Pa (re) = 100, and when maM and maoM (re) are farthest, theoretically Since the peak position difference | maM−maoM (re) | = MA−1 and the peak position correlation Pa (re) is approximately −300, the peak position correlation Pa (re) is theoretically −300 <Pa ( re) takes a value of ≦ 100. However, since it is rare that the peak position difference | maM−maoM (re) | exceeds MA / 2 based on experience, the peak position correlation Pa (re) is normally −100 <Pa (re) ≦ 100. Takes a value. The peak position correlation Pa (re) is a value that increases as the peak position difference | maM−maoM (re) | becomes smaller, and is determined based on the peak position difference.

  Next, the frequency distribution matching unit 40 compares the peak position correlation Pa (re) of the area ratio distribution calculated in step S680 with the determination threshold (step S690). If the peak position correlation Pa (re) is greater than or equal to the determination threshold, it is determined to be suitable, and if the peak position correlation Pa (re) is smaller than the determination threshold, it is determined to be non-conforming. The determination threshold can be arbitrarily set as long as it is a positive value, but here it is +50.0. If it is determined to be suitable in step S690, the frequency distribution matching unit 40 determines that the output should be restricted (output inappropriate) because the target model and the restriction model of the record re are compatible. Do. FIG. 17 is a diagram illustrating the relationship between the circumscribed circle distribution (histogram) and the peak position. In FIG. 17, the left side shows the restriction model, and the right side shows the target model. If it is determined to be suitable in step S690, the frequency distribution matching unit 40 determines that the output should be restricted (output inappropriate) because the target model and the restriction model of the record re are compatible. Do.

  In the present embodiment, as described with reference to FIG. 16, the frequency distributions are collated using two methods of the peak position correlation and the correlation coefficient. However, it is not always necessary to use the two methods, and the frequency distribution may be verified using either the peak position correlation or the correlation coefficient. When either one is used, the correlation coefficient is considered to be more accurate, but even with the use of the peak position correlation, it is possible to perform collation with considerably high accuracy.

  If it is determined as non-conforming in any one of steps S630, S650, S670, and S690, the frequency distribution matching unit 40 finishes matching the target model with the restriction model of the record re, and compares it with the restriction model of the next record re + 1. Move on to verification. When the process according to the flowchart of FIG. 16 is executed for all records in the restriction model database 60 and there is at least one applicable restriction model, the output should be restricted to the target model (output) Inappropriate) ”, the collation process in step S200 is terminated.

<Data output to 4.3D printer>
In step S200, if the frequency distribution matching unit 40 determines that “the output should not be restricted (output appropriate)”, the target model is output to the 3D printer 7 which is a three-dimensional object formation apparatus. That is, the target model that is a polygon model whose output is permitted by the three-dimensional object modeling data output restriction device is output to the three-dimensional object modeling device that models the three-dimensional object. On the other hand, if the frequency distribution matching means 40 determines that “the output should be regulated (output inappropriate)”, the target model is not output to the 3D printer 7 which is a three-dimensional object shaping apparatus. If it takes a long time to determine whether output is appropriate or not, whether the target model is output to the 3D printer 7 and whether the output is appropriate or inappropriate in parallel with the output process (three-dimensional object modeling process) of the 3D printer 7. If the output is unsuitable, an output stop command may be output to the 3D printer 7. At this time, from the user's point of view, it is only possible to confirm that the three-dimensional object shaping process in the 3D printer is started by issuing a single command to output the target model. I do not notice that the execution of the process for is started.

<5. Calculation and registration of regulatory model frequency distribution>
As a modified example, the circumscribed circle distribution and the area ratio distribution calculated with respect to the restriction model are output to the three-dimensional object formation data output at a place different from the three-dimensional object formation data output restriction device provided with the frequency distribution matching means 40. You may make it register and transmit to a control apparatus via a network.

  FIG. 18 is a hardware configuration diagram of a three-dimensional object formation system including a three-dimensional object formation data output restriction device according to a modification. In the three-dimensional object formation system shown in FIG. 18, the three-dimensional object formation data output restriction device 101 communicates with a public network such as the Internet in the configuration of the three-dimensional object formation data output restriction device 100 shown in FIG. 3. The network communication unit 8 is provided. The regulation model frequency distribution calculating device 102 can be realized by a general-purpose computer. As shown in FIG. 18, a CPU (Central Processing Unit) 1a, a RAM (Random Access Memory) 2a that is a main memory of the computer, A large-capacity storage device 3a such as a hard disk or flash memory for storing programs and data executed by the CPU 1a, a key input I / F (interface) 4a such as a keyboard and a mouse, and an external device such as a data storage medium A data input / output I / F (interface) 5a for data communication, a display unit 6a that is a display device such as a liquid crystal display, and a network communication unit 8a for communicating with a public network such as the Internet are provided. Connected through. The network communication unit 8 of the three-dimensional object formation data output restriction device 101 and the network communication unit 8a of the restriction model frequency distribution calculation device 102 communicate with each other, and the restriction model frequency distribution calculation device 102 transmits the three-dimensional object formation data output restriction device 101. Thus, it is possible to transmit two types of frequency distributions calculated for the regulatory model.

  In FIG. 18, the three-dimensional object formation data output restriction device 101 and the 3D printer 7 are shown in a separated form. However, most of the currently available 3D printer products include the three-dimensional object formation data output restriction device 101. Constituent elements, such as CPU1, RAM2, storage device 3, key input I / F4 (not a keyboard / mouse for general-purpose computers, but several buttons at a numeric keypad level), data input / output I / F5, display unit 6 (several lines) A small liquid crystal panel capable of displaying the above-mentioned characters, a touch panel is often overlapped to serve also as a key input I / F 4), and a network communication unit 8 (wireless LAN function) is also provided in a small but overlapping manner. Accordingly, the 3D printer itself can directly receive the data for modeling a three-dimensional object via an external storage medium or the Internet, and can be operated to model a three-dimensional object alone (especially in the case of a 3D printer for consumer use, this form is preferred. Many). That is, in many cases, the three-dimensional object formation data output restriction device 101 and the 3D printer 7 shown in FIG. 18 are housed in one housing and distributed as a product called “3D printer”.

  In the regulated model frequency distribution calculation device 102, the CPU 1a executes a program stored in the storage device 3a, thereby realizing a second frequency distribution calculation unit and a frequency distribution transmission unit. The second frequency distribution calculation means realized by the restriction model frequency distribution calculation device 102 has the same function as the frequency distribution calculation means 10 realized by the three-dimensional object formation data output restriction device 100, and is compatible with the restriction model. The circumscribed circle distribution and the area ratio distribution are calculated as the two types of frequency distribution. The frequency distribution transmission unit transmits the circumscribed circle distribution and the area ratio distribution, which are two types of frequency distributions calculated for the restriction model, to the three-dimensional object formation data output restriction device 101. In the three-dimensional object shaping data output restriction device 101, when the network communication unit 8 receives the frequency distribution from the restriction model frequency distribution calculation device 102, the CPU 1 executes a predetermined program and functions as a frequency distribution registration unit. The frequency distribution is registered in the regulation model database 60 realized by the storage device 3.

<6. Cloud-type 3D object modeling system>
The present invention can also be applied to a cloud-type three-dimensional object modeling system. “Cloud type 3D object modeling system” means that when the target model requested by the user is raised to the cloud, it will be checked for output on the cloud (including manual visual inspection and 3D printer output consistency check) Generally used in the sense of 3D printer consignment output service that outputs the 3D object modeling of the permitted target model with a 3D printer on the cloud and returns the output modeling object to the client. In this application, the former output The focus is on conducting a pass / fail examination on a remote computer on the cloud, and it is not essential to perform solid object modeling (3D printer output) on the cloud. FIG. 19 is a hardware configuration diagram of a cloud-type three-dimensional object modeling system. In the three-dimensional object formation system shown in FIG. 19, the three-dimensional object formation data output restriction device is realized by the output control terminal 201 and the processing server 202. In the three-dimensional object modeling system shown in FIG. 19, the output control terminal 201 has a hardware configuration equivalent to the computer shown as the three-dimensional object modeling data output restriction device 101 in FIG. 18. That is, the output control terminal 201 includes a CPU 11, a RAM 12, a storage device 13, a key input I / F 14, a data input / output I / F 15, a display unit 16, and a network communication unit 18, which are connected to each other via a bus. .

  The processing server 202 can be realized by incorporating a dedicated program into a general-purpose computer. As shown in FIG. 19, a CPU 11a, a RAM 12a, a storage device 13a, a key input I / F 14a, a data input / output I / F 15a, a display unit 16a, and a network communication unit 18a are connected to each other via a bus. The network communication unit 18 of the output control terminal 201 and the network communication unit 18a of the processing server 202 communicate with each other, and send output suitability data from the processing server 202 to the output control terminal 201 based on the judgment of output suitability. It is possible. In FIG. 19, the output control terminal 201 and the 3D printer 7 are shown in a separated form. However, as in the example of FIG. 18, the CPU 11, the RAM 12, and the constituent elements of the output control terminal 201 are included in the 3D printer product. The storage device 13, the key input I / F 14, the data input / output I / F 15, the display unit 16, and the network communication unit 18 may be provided in an overlapping manner.

  FIG. 20 is a functional block diagram of a cloud-type three-dimensional object modeling system. The processing server 202 constituting the cloud-type three-dimensional object modeling system includes a target model receiving unit 70 and an output propriety data transmitting unit 80 in addition to each unit of the three-dimensional object modeling data output restriction device shown in FIG. It has a configuration. The target model storage unit 51 stores not the target model itself but two kinds of frequency distributions calculated for the target model. Further, the frequency distribution calculating means 10 is configured to be provided not in the processing server 202 but in the output control terminal 201.

  Components having the same functions as those of the three-dimensional object formation data output restricting device shown in FIG. The target model receiving means 70 is means for receiving the frequency distribution of the target model transmitted from the output control terminal 201 and registering it in the target model storage means 51. The CPU 11a executes a predetermined program, and the network communication section This is realized by controlling 18a. The output suitability data transmission means 80 is means for sending output suitability data to the output control terminal 201 based on “whether or not the output should be regulated” determined by the frequency distribution matching means 40, and the CPU 11a This is realized by executing a predetermined program and controlling the network communication unit 18a.

  The processing server 202 is a cloud computer connected to a network such as the Internet and can be accessed from a number of output control terminals. In the conventional server type computer, when the access of many users is concentrated, the responsiveness becomes slow and it often causes trouble for the user. In the cloud type, the physical configuration of the computer is dynamically changed by the virtualization technology. This makes it possible to always maintain a stable response. Generally, the processing server 202 is physically realized by a plurality of computers.

  The processing operation of the cloud-type three-dimensional object modeling system shown in FIGS. 19 and 20 will be described. In the output control terminal 201, when the user specifies a target model to be output via the key input I / F 14, the CPU 11 extracts the specified target model stored in the storage device 13 and specifies the target model. A model ID which is identification information to be assigned is assigned. Then, the CPU 11 performs processing on the target model to which the model ID is assigned, according to the flowchart shown in FIG. 7 or FIG. 13, and the frequency configured by the circumscribed circle distribution and the area ratio distribution. Generate a distribution. Further, the CPU 11 transmits the generated frequency distribution to an address such as a URL set in advance in the storage device 13 via the network communication unit 18. By using a method of transmitting a frequency distribution with a significantly smaller amount of information than polygon data, not only the transmission time is greatly shortened, but also the polygon data that is a copyrighted work is not transmitted to the processing server 202 side. Since no copy remains on the processing server 202 side, copyright infringement can be avoided.

  In parallel, the CPU 11 transmits the target model to which the model ID is assigned to the data processing unit 7a of the 3D printer 7 via the data input / output I / F 15. The target model received from the output control terminal 201 is held in the printer queue in the data processing unit 7a, and enters a standby state as an output job. At this time, it is possible to execute only the process of converting the polygon format data, which is the pre-processing in the 3D printer output, into the data in the stack format, and to enter the standby state when the data is converted into the stack format data. . Since this data processing load is also reasonably high, if the output suitability determination is completed during this time, it is possible to prevent the user from feeling an extra waiting time.

  In the processing server 202, when the target model receiving unit 70 receives the frequency distribution of the target model transmitted from the output control terminal 201, the target model storage unit 51 stores the frequency distribution in the target model storage unit 51. Here, according to the flowchart shown in FIG. 5, the frequency distribution matching unit 20, the frequency distribution emphasizing unit 30, and the frequency distribution matching unit 40 perform processing to determine whether the output of the target model corresponding to the received frequency distribution is appropriate. Output propriety data as a result of output propriety is passed from the frequency distribution matching unit 40 to the output propriety data transmitting unit 80. Then, the output suitability data transmission unit 80 transmits the output suitability data with the model ID added to the output control terminal 201 which is the transmission source (access source) of the frequency distribution.

  In the output control terminal 201, when the network communication unit 18 receives the output suitability data from the processing server 202, the CPU 11 sends the received output suitability data to the data processing unit 7a of the 3D printer 7 via the data input / output I / F 15. Send to. The data processing unit 7a refers to the output job in the printer queue by using the model ID given to the received output suitability data. If the output suitability data is “appropriate (output proper)”, the data processing unit 7a changes the output job from the standby state to the output state, and outputs the target model to the output unit 7b. If the output suitability data is “No (output unsuitable)”, the data processing unit 7a discards the output job. That is, it is deleted from the printer queue.

<7. Matching case>
21 and 22 show a comparative case and a matching case 1 according to the present invention. In both FIG. 21 and FIG. 22, the 3D sphere model b is shown as an example collated with the 3D sphere model a and the 3D master model. The upper row shows the appearance of each polygon model, and the lower row shows two types of frequency distributions obtained from each polygon model. In the comparative example in FIG. 21, the two types of frequency distributions are a frequency distribution with a circumscribed circle radius on the upper side (circumscribed circle distribution) and a frequency distribution with an inscribed circle radius on the lower side (inscribed circle distribution). The two frequency distributions are the circumscribed circle distribution on the upper side and the area ratio distribution on the lower side in the matching example 1 in FIG. The 3D sphere model a and the 3D sphere model b imitate a sphere, but to be precise, it is a regular polyhedron polygon model. The 3D sphere model a is composed of 5040 polygons, and the 3D sphere model b is composed of 120 polygons. . The 3D Takuma model is a polyhedral polygon model that imitates Takuma and is composed of 15944 polygons.

  In the figure, the values of Corr (D, A) and Peak (D, A) described in two middle stages are the values before performing the enhancement process (described in the center of the middle stage) and after performing the enhancement process (middle stage). (Corresponding to the right end of FIG. 4) shows the matching result between the frequency distributions shown above and below, Corr (D, A) shows correlation coefficients Dd (re) and Da (re), and Peak (D, A) shows , Peak position correlations Pd (re) and Pa (re) are shown, respectively. In FIG. 21, the value D indicates the result of matching the circumscribed circle distribution, and the value A indicates the result of matching the frequency distribution of the inscribed circle radius. In FIG. 22, the value D represents the matching result of the circumscribed circle distribution, and the value A represents the matching result of the area ratio distribution.

  Since both the 3D sphere model a and the 3D sphere model b imitate a sphere, it is preferable that the correlation between them increases. On the other hand, since the 3D sphere model b and the 3D polishing model imitate completely different shapes, it is preferable that the correlation be low. Comparing the comparison results of the 3D sphere model a and the 3D sphere model b with FIG. 21 and FIG. 22, in particular, regarding the area ratio distribution, the present invention has a correlation between both the correlation coefficient and the peak position correlation. It can be seen that is increasing. The reason is that the inscribed circle distribution in FIG. 21 is a wide distribution that is significantly different from the circumscribed circle distribution, and a difference is seen between the 3D sphere model a and the 3D sphere model b. On the other hand, the area ratio distribution in FIG. 22 is similar to the circumscribed circle distribution, and there is almost no difference between the 3D sphere model a and the 3D sphere model b. Comparing the comparison results of the 3D sphere model b and the 3D duffing model, FIG. 21 and FIG. You can see that it is getting smaller. The reason is that the inscribed circle distribution of the 3D polishing model in FIG. 21 and the area ratio distribution of the 3D polishing model in FIG. 22 are similar in peak position, but there is a difference in the spread of the distribution. The inscribed circle distribution is wider than the inscribed circle distribution. Therefore, the difference from the inscribed circle distribution of the 3D sphere model b in FIG. 21 is not so large. On the other hand, the area ratio distribution of the 3D polishing model of FIG. 22 is a sharp distribution similar to the circumscribed circle distribution, and the peak position is significantly different from the area ratio distribution of the 3D sphere model b of FIG. There is a big difference between the 3D Tadashi model. From the above, it can be seen that the identification accuracy is more improved in the present invention using the area ratio distribution than in the other methods.

  FIG. 23 shows a matching case 2 according to the present invention. FIG. 23 shows a case where the 3D sphere model a is collated with the 3D cylindrical model and the 3D ellipsoid model. The two frequency distributions are a circumscribed circle distribution on the upper side and an area ratio distribution on the lower side in the collation example in FIG. The 3D sphere model a is the same as that shown in FIGS. 21 (a) and 22 (a). The 3D cylinder model imitates a cylinder, but it is precisely a polygon model of a polygonal cylinder. The 3D ellipsoidal model imitates an elliptical sphere that is obtained by squashing the 3D sphere model a in the vertical direction, but it is precisely a polyhedral polygon model. The 3D sphere model a is composed of 5040 polygons, the 3D cylinder model is composed of 288 polygons, and the 3D ellipsoidal model is composed of 5040 polygons.

  Looking at the collation result between the 3D sphere model a and the 3D cylinder model, it can be seen that although the peak positions of the circumscribed circle distribution are shifted, the distribution shapes are similar, and the peak position correlation shows a positive value. This alone may result in misjudgment that the two are similar. On the other hand, regarding the area ratio distribution, the peak position and the distribution shape are completely different, and both values of the correlation coefficient and the peak position correlation show negative values, and it can be determined that both are incompatible. That is, it can be seen that the difference between the 3D sphere model a and the 3D cylinder model cannot be determined only by the circumscribed circle distribution. Subsequently, when the comparison result between the 3D sphere model a and the 3D ellipsoid model is seen, the area ratio distribution is almost the same in both the peak position and the distribution shape, and both the correlation coefficient and the peak position correlation are high positive values. Since it shows a value, it is determined that both are compatible. On the other hand, with respect to the circumscribed circle distribution, the peak position and the distribution shape are completely different, and both the correlation coefficient and the peak position correlation are negative values. That is, it can be seen that the difference between the 3D sphere model a and the 3D ellipsoid model cannot be determined only by the area ratio distribution. Therefore, for example, when the frequency distribution is registered in the database using the 3D sphere model a as the restriction model, both the circumscribed circle distribution and the area ratio distribution are registered, and the 3D cylinder model and the 3D ellipsoid model are the target models. As described above, when determining whether or not the output is appropriate in the three-dimensional object shaping data output restriction device of the present embodiment, both the 3D ellipsoid model and the 3D cylinder model are output unless collation is performed using both the circumscribed circle distribution and the area ratio distribution. Appropriate (nonconforming) is not properly determined.

  The three-dimensional object shaping data output restriction device 100 not only determines conformity / nonconformity, but also the peak position correlation and correlation calculated by the frequency distribution matching means 40 in steps S620, S640, S660, and S680 shown in FIG. The display unit 6 can output the numbers and the like. By visually confirming the peak position correlation and the correlation coefficient displayed and output by the display unit 6, for example, in the case of non-conformity, it is possible to determine not only the non-conformity but also the degree of the non-conformity. .

<8. Modified example>
The preferred embodiments of the present invention have been described above. However, the present invention is not limited to the above embodiments, and various modifications can be made. For example, in the above embodiment, the polygon to be processed is a triangle, but it may be a polygon more than a quadrangle.

  Further, in the above embodiment, the matching is performed using the circumscribed circle distribution and the area ratio distribution as the two types of frequency distributions. However, the matching is performed using only the area ratio distribution without using the circumscribed circle distribution, and output. You may make it determine suitability. When both the circumscribed circle distribution and area ratio distribution are used, the accuracy of matching is further increased. However, even if only the area ratio distribution is used, output suitability is determined with high accuracy depending on the characteristics of the polygon model to be matched. can do.

  In the above embodiment, the polygon center of gravity having the average coordinates of each vertex of the polygon is used as one point on the polygon for forming the triangle. When the center of gravity is used, the shape is not limited to a triangular shape and can be applied to a polygon having an arbitrary number of vertices, but may be a point other than the center of gravity of the polygon as long as it is a point on the polygon. For example, as a point on the polygon, a point having a value that is exactly halfway between the maximum value and the minimum value of the vertex of the polygon for each xyz coordinate can be used.

  Further, in the above embodiment, when the restriction model is composed of a plurality of parts and the target model is one part of the restriction model, the frequency distribution scale of the target model is changed to the scale of the restriction model in order to realize partial matching between the two. After matching the frequency distribution to be matched to each of the frequency distributions, each frequency distribution is multiplied by the emphasis component, and the emphasis frequency distribution of the target model and the emphasis frequency distribution of the regulatory model are collated. When performing full matching between the model and the target model, the frequency distribution matching and emphasis processing is not performed, and the frequency distribution of the target model and the frequency distribution of the regulatory model extracted from the database are only correlation coefficients. You may make it collate using.

  In the above embodiment, for calculating the frequency distribution based on the value obtained by dividing the area of the circumscribed circle of the triangle by the square root of the area of the triangle between the polygons, The pseudo area ratio obtained by dividing the square of (the area of the circumscribed circle by π) by the square root of the triangular area was calculated. However, it is not limited to the one shown in [Formula 10] for calculating the area ratio distribution, and may be one obtained by multiplying an appropriate coefficient.

1, 1a, 11, 11a... CPU (Central Processing Unit)
2, 2a, 12, 12a ... RAM (Random Access Memory)
3, 3a, 13, 13a ... Storage device 4, 4a, 14, 14a ... Key input I / F
5, 5a, 15, 15a ... Data I / O I / F
6, 6a, 16, 16a ... display unit 7 ... 3D printer (three-dimensional object modeling apparatus)
7a: Data processing unit 7b: Output unit 8, 8a, 18, 18a: Network communication unit 10: Frequency distribution calculating means (frequency distribution calculating device)
20 ... Frequency distribution matching means 30 ... Frequency distribution enhancement means 40 ... Frequency distribution matching means 50, 51 ... Target model storage means 60 ... Regulatory model database 70 ... Target model receiving means 80 ... Output propriety data transmission means 100, 101 ... Solid object shaping data output restriction device 102 ... Restriction model frequency distribution calculation device 201 ... Output control terminal 202 ... Processing server

Claims (22)

A device for determining whether or not to regulate when outputting a polygon model expressed as a set of polygons to a three-dimensional object modeling apparatus as three-dimensional object modeling data,
Area that is a frequency distribution based on a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in a restriction model that is a polygon model whose output is to be restricted, by the square root of the area of the triangle A database in which the ratio distribution is registered;
Based on a target model which is a polygon model to be output, a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the target model by the square root of the area of the triangle A frequency distribution calculating means for calculating an area ratio distribution which is a frequency distribution;
A frequency distribution matching unit that collates the area ratio distribution of the target model with the area ratio distribution of the regulation model and determines whether or not the output should be regulated;
A data output regulating device for three-dimensional object formation characterized by comprising:   In calculating the area ratio distribution, the frequency distribution calculating unit prepares a one-dimensional array composed of a predetermined number of elements, and calculates the range of the square of the maximum value of the calculated radius of the circumscribed circle. After equally dividing into a predetermined number, each area ratio is assigned to one of the predetermined elements based on the value of the area ratio, and the area ratio distribution is calculated by the number corresponding to the element. The three-dimensional object modeling data output restriction device according to claim 1, wherein:   The frequency distribution calculating means obtains polygons in the target model in units of three for the target model, randomly classifies them into three groups, a first group, a second group, and a third group, 3. The three-dimensional object formation data output restriction device according to claim 1, wherein the three polygons are selected by selecting polygons one by one from the group.   The frequency distribution calculating means creates a random number array in which N / 3 consecutive integers are randomly replaced when the number of polygons in each group is N / 3, and from the beginning to the end of the random number array. The reverse random number array is created by reversing the order of the above, and the random number array is applied to one of the three groups, and the reverse random number array is applied to the other group, and the order of the polygons in the group is determined. 4. The three-dimensional object formation data output restriction device according to claim 3, wherein the polygons are selected in order from the top of each group after the replacement. The frequency distribution calculating means includes:
The random number array is applied to the first group of polygons and the inverted random number array is applied to the second group of polygons to change the order, and the polygons are selected without changing the order of the third group of polygons. N / 3 triangles are formed,
The random number array is applied to the second group of polygons and the inverted random number array is applied to the third group of polygons to change the order, and the polygons are selected without changing the order of the first group of polygons. N / 3 triangles are formed,
The random number array is applied to the third group of polygons and the inverted random number array is applied to the first group of polygons to change the order, and the polygons are selected without changing the order of the second group of polygons. 5. The three-dimensional object formation data output restriction device according to claim 4, wherein N / 3 triangles are formed. The frequency distribution calculating means includes:
Each time the area ratio distribution is calculated, the calculation of the area ratio distribution is repeated a predetermined number of times by changing the order of polygons in two of the three groups. 6. The three-dimensional object shaping data output regulating device according to claim 4, wherein the average value of the area ratio distribution is an area ratio distribution to be verified. The frequency distribution calculating means includes:
Each time the area ratio distribution is calculated, the order of polygons in two groups of the three groups is changed, and the process of calculating the area ratio distribution is repeated.
When the area ratio distribution immediately after the calculation is compared with the area ratio distribution obtained immediately before the comparison, and the similarity is recognized as a result of the comparison, the area ratio distribution immediately after the calculation is referred to as the area ratio distribution to be verified. The three-dimensional object formation data output restriction device according to claim 4 or 5, wherein In the database, in addition to the area ratio distribution, a circumscribed circle distribution that is a frequency distribution of the radius of the circumscribed circle of the triangle is registered.
The frequency distribution calculating means calculates a circumscribed circle distribution that is a frequency distribution of the radius of the circumscribed circle of the triangle in addition to the area ratio distribution for the target model,
The frequency distribution matching means, in addition to the verification of the area ratio distribution, compares the circumscribed circle distribution of the target model with the circumscribed circle distribution of the restriction model, and determines whether or not the output should be regulated. The three-dimensional object formation data output regulation device according to any one of claims 1 to 7, wherein   In calculating the circumscribed circle distribution, the frequency distribution calculating unit prepares a one-dimensional array composed of a predetermined number of elements, and sets the range of the calculated maximum value of the radius of the circumscribed circle to the predetermined number. After dividing equally, the radius of each circumscribed circle is assigned to any one of the predetermined number of elements based on the value of the radius of the circumscribed circle, and the circumscribed circle distribution is calculated based on the number corresponding to the element. The three-dimensional object modeling data output regulation device according to claim 8.   The frequency distribution calculating means multiplies the area of the polygon by an inner product value of a unit vector from the center of gravity of a triangle formed by a predetermined point of the three polygons to each vertex and a normal vector of the polygon including the vertex. The three-dimensional object formation data output restriction device according to claim 9, wherein an average value of the obtained values is calculated as a weight value, and weighting is performed using the weight value when obtaining a number corresponding to the element.   The frequency distribution calculating means divides the value of each element by the sum of the weight values for each polygon constituting each target model, and gives the absolute value if the element is a negative value The data output regulation apparatus for three-dimensional object formation according to claim 10, wherein the frequency distribution is calculated. A process of matching the scale of the radius of the circumscribed circle of the frequency distribution of the target model with the scale of the radius of the circumscribed circle of the frequency distribution of the regulatory model registered in the database, and the frequency of the matched target model A frequency distribution matching means for creating a distribution;
The frequency distribution collating means collates the frequency distribution of the matched target model with the frequency distribution of the restriction model, and determines whether or not the output should be regulated. The data output regulation apparatus for solid object modeling as described in any one of these. With respect to the frequency distribution of the target model and the frequency distribution of the regulation model, the smaller the value of the element, the larger the value and the multiplication of the emphasis component that takes a value greater than 0 and less than or equal to 1, respectively. And a frequency distribution emphasizing means for creating an emphasis frequency distribution of the regulatory model,
13. The three-dimensional object formation data output restriction device according to claim 12, wherein the frequency distribution collating unit collates the enhancement frequency distribution of the target model with the enhancement frequency distribution of the restriction model.   The frequency distribution collating means calculates a correlation coefficient between the frequency distributions when collating the frequency distribution of the target model with the frequency distribution of the regulatory model, and outputs an output based on the calculated correlation coefficient. The three-dimensional object formation data output restriction device according to any one of claims 1 to 13, wherein it is determined whether or not the restriction is to be performed.   The frequency distribution matching means calculates a peak position that gives the maximum value when matching the frequency distribution of the target model with the frequency distribution of the regulatory model, and outputs an output based on the difference between the calculated peak positions. The three-dimensional object formation data output restriction device according to any one of claims 1 to 14, wherein it is determined whether or not the restriction is to be performed.   An area ratio that is a frequency distribution based on a value obtained by dividing an area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the restriction model by a square root of the area of the triangle with respect to the restriction model 16. The apparatus according to claim 1, further comprising a registration unit that receives the frequency distribution calculated by the regulatory model frequency distribution calculation device that calculates the distribution and registers the received frequency distribution in the database. The data output restriction apparatus for three-dimensional object modeling according to one item.   The regulation model frequency distribution calculating device acquires polygons in the regulation model in units of three for the regulation model, and randomly classifies them into three groups of a first group, a second group, and a third group. The three-dimensional object shaping data output restriction device according to claim 16, wherein the three polygons are selected by selecting one polygon from each group. Means for outputting the target model to a connected three-dimensional object shaping apparatus;
When it is determined that the output should be regulated by the frequency distribution matching unit that is executed in parallel with the three-dimensional object modeling process by the three-dimensional object modeling apparatus, the three-dimensional object modeling apparatus includes the target model. Means for outputting an output stop command;
The three-dimensional object formation data output restriction device according to any one of claims 1 to 17, further comprising: The output control terminal and the processing server are connected via a network,
The output control terminal has the frequency distribution calculating means,
The processing server
The database;
Receiving means for receiving an area ratio distribution of the target model from the output control terminal via a network;
The frequency distribution matching means;
Output suitability data transmission means for transmitting data based on whether the output should be regulated or not, determined by the frequency distribution matching means, to the output control terminal;
The three-dimensional object formation data output restriction device according to any one of claims 1 to 18, wherein the three-dimensional object formation data output restriction device is provided. A data output regulation device for three-dimensional object modeling according to any one of claims 1 to 19,
A three-dimensional object modeling apparatus that models a three-dimensional object using a polygon model whose output is permitted by the three-dimensional object modeling data output restriction device;
A three-dimensional object forming system characterized by comprising: A device that calculates a frequency distribution based on the polygon model in order to determine whether or not to regulate when a polygon model expressed as a set of polygons is output to the three-dimensional object modeling apparatus as three-dimensional object modeling data. There,
Based on a target model which is a polygon model to be output, a value obtained by dividing the area of a circumscribed circle of a triangle formed by predetermined points of three polygons in the target model by the square root of the area of the triangle A frequency distribution calculation device that calculates an area ratio distribution that is a frequency distribution.   A program for causing a computer to function as the three-dimensional object formation data output restriction device according to any one of claims 1 to 19.