WO2006109394A1

WO2006109394A1 - 3-dimensional shape detection device and 3-dimensional shape detection method

Info

Publication number: WO2006109394A1
Application number: PCT/JP2006/305105
Authority: WO
Inventors: Xiaolin Zhang; Takuro Kawai; Makoto Sato; Tsuyoshi Kobayashi
Original assignee: Xiaolin Zhang; Takuro Kawai; Makoto Sato; Tsuyoshi Kobayashi
Priority date: 2005-03-16
Filing date: 2006-03-15
Publication date: 2006-10-19
Also published as: JP4243692B2; CN101133299B; JP2006258543A; CN101133299A

Abstract

There are provided a 3-dimensional shape detection device and a 3-dimensional shape detection method capable of performing real time processing by accurately corresponding a reference point in an edge image with a simple process. An object (20) is imaged from at least two predetermined imaging positions by a camera unit (10) so as to detect the 3-dimensional shape of the object (20). The camera unit (10) has a lens (1) and an imaging element (2). A visual axis micro-motion device (4) micro- moves the optical axis of the camera unit (10) in the direction connecting the imaging positions. A plurality of images captured here are subjected to an image processing such as edge emphasis by an image processing unit (3) so as to generate an edge image in which the edge of the object (20) is extracted. The edge images from the two imaging positions are compared to detect the corresponding edge of the object (20).

Description

Specification

Three-dimensional shape detection apparatus and three-dimensional shape detection method

Technical field

TECHNICAL FIELD [0001] The present invention relates to an apparatus and method for detecting a three-dimensional shape, and in particular, generates an edge image having distance information by minutely moving the optical axis of a camera and uses this to associate reference points.ヽ, a solid shape detection apparatus and a solid shape detection method for detecting a solid shape.

Background art

Conventionally, various methods for detecting the shape of a solid from two images using parallax have been developed. Usually, using the principle of triangulation, the target object is photographed by two cameras placed at two known positions, the reference point (corresponding point) of the target object is determined, and each camera By aligning the reference point of the captured target object and obtaining the parallax of other parts, the camera power can detect the distance to each edge of the target object.

Here, in order to obtain the parallax, it is necessary to determine a reference point indicating the same position of the target object from the image of the target object photographed by each camera. If the reference point is set at a different position on the target object, the 3D shape will be mistaken and the correct shape will not be detected. This is a very important issue, and various solutions to this problem are also proposed. Has been. For example, the relative difference in position in the X-axis direction between each pixel on another edge relative to each pixel on one edge corresponds to the parallax, and the edges of the two edge images correspond to edges on the same line of the target object If so, there is a technique that uses the principle that the parallax of pixels on the edge is almost uniform at any position in the y-axis direction.

[0004] Further, as described in Patent Document 1, a relative difference is obtained for each pixel constituting the edge of two edge images, and weighting is performed based on partial information on density regarding each pixel. Some have tried to determine the corresponding reference point more accurately.

Patent Document 1: JP-A-6-180218

Disclosure of the invention

Problems to be solved by the invention [0005] However, even if the corresponding reference point is accurately obtained in the conventional method, a large amount of calculation is required for this, and the processing time is increased. Therefore, it was difficult to detect the three-dimensional shape in real time by photographing the moving object using two cameras because of the processing time.

In view of such circumstances, the present invention is to provide a three-dimensional shape detection apparatus and a three-dimensional shape detection method capable of performing real-time processing by accurately associating reference points in an edge image with simple processing. It is what.

Means for solving the problem

In order to achieve the object of the present invention described above, a three-dimensional shape detection apparatus according to the present invention is an image sensor for photographing a target object from at least two predetermined photographing positions having different lines of sight to the target object. And at least one camera means having a lens, visual axis fine movement means for minutely moving the optical axis of the camera means in a direction connecting the at least two predetermined photographing positions, and an optical axis by the visual axis fine movement means Image processing is performed on a plurality of images from the camera means that are moved slightly, thereby generating edge images in which the edges of the target object at the at least two predetermined shooting positions are extracted, respectively, And an image processing means for detecting a corresponding edge of the target object by comparing the edge images.

Here, the predetermined photographing position may be arranged along at least one direction in the horizontal direction, the vertical direction, the oblique direction, or a plurality of these directions.

[0009] Further, it may have moving means that can move the camera means to a predetermined photographing position.

[0010] Further, the camera means may have at least two camera forces, and each camera may be arranged in advance at a predetermined shooting position.

[0011] The at least two camera means may be synchronized with each other, and may be simultaneously photographed with the same minute movement.

[0012] Further, the visual axis fine movement means may move the lens minutely or move the camera means minutely.

In addition, the visual axis fine movement means includes a piezoelectric element, a giant magnetostrictive element, an electrostatic actuator, a hydraulic actuator, a pneumatic actuator, an electromagnet, an optical actuator, a shape memory alloy, and a polymer. It should be composed of any power of the actuator.

Here, the minute movement by the visual axis fine movement means may be a translational movement in the normal direction of the optical axis of the camera means.

[0015] Further, the fine movement by the visual axis fine movement means may be a rotational movement around a predetermined point. The rotational angle of the rotational motion at that time may be an angle such that the movement width of the target object close to infinity on the image sensor is 0 to 3 pixels.

[0016] Further, the three-dimensional shape detection method according to the present invention includes a process of photographing a target object with at least one camera means having an imaging element and a lens from at least two predetermined photographing positions having different lines of sight to the target object. A step of minutely moving the optical axis of the camera means in a direction connecting the at least two predetermined photographing positions during the photographing step, and a plurality of from the camera means in which the optical axis is minutely moved. The image processing is performed on each of the images to generate an edge image in which the edge of the target object is extracted at the at least two predetermined shooting positions, and the corresponding edge object is compared with each other to correspond to the target object. And a process of detecting an edge.

[0017] Here, in the process of generating the edge image, normal density may be performed by differentially processing the grayscale value or the saturation value of each corresponding pixel of the plurality of images. Furthermore, binarization processing may be added.

[0018] Further, in the process of detecting the corresponding edge, the edge of the edge image at the at least two predetermined photographing positions may be associated with each other based on the width and length of the edge of the edge image.

Further, the process of detecting the corresponding edge may be performed by a pattern matching method.

[0020] The process of detecting the corresponding edge may be based on the direction of the line of sight to the target object. In this case, the edges of the generated edge image may be converted into a predetermined reference width based on the direction of the line of sight to the target object, and the edge images may be compared.

The invention's effect

[0021] The three-dimensional shape detection apparatus and the three-dimensional shape detection method of the present invention include an ET having distance information. Therefore, there is an advantage that the corresponding edge can be easily detected by focusing only on the edge width and length of the edge image. In addition, since it can be easily detected, there is an advantage that real-time processing with a short processing time is possible.

BEST MODE FOR CARRYING OUT THE INVENTION

[0022] The human eyeball is like tremor, which is a very small high-frequency vibration, drift, which is a small smooth movement, and a micro saccade, which is a linear movement. Microvibration is constantly performed unconsciously. The effects of such micro-vibrations on visual recognition! / ?! As a result, a lot of research has been conducted on both physiological and engineering forces. It is considered as a movement for detecting depth. Of these human eyeball movements, we focused on the movement of the microsaccade, and developed a device and method that can detect three-dimensional shapes with high accuracy and speed using the same movement as the microsaccade.

Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings. FIG. 1 is a schematic diagram for explaining details of a camera unit used in the three-dimensional shape detection apparatus of the present invention. As shown in the figure, the camera unit 10 also has a force with the lens 1 and the image sensor 2. The lens may be a short focus lens or a zoom lens, and the angle of view may be wide or narrow. These may be variously changed or selected depending on the purpose of use of the three-dimensional shape detection apparatus, the distance to the target object, and the like. The image sensor 2 is a photoelectric conversion element such as a CCD or CMOS, and converts an image formed on the image sensor by a lens into an electric signal. Then, the image processing unit 3 connected to the image sensor 2 generates an image using the electric signal from the image sensor.

The visual axis fine movement device 4, which is a characteristic part of the present invention, is connected to the camera unit 10. The visual axis fine movement device 4 causes the camera unit to vibrate laterally with respect to the optical axis, and the optical axis of the camera unit is slightly moved laterally. The vibration frequency is not particularly limited. For example, it may be appropriately vibrated at several Hz to several tens Hz. This can be variously set in consideration of the follow-up performance to the moving speed of the target object. Then, a plurality of target objects are photographed by the camera unit 10 while the optical axis of the camera unit is vibrating. It should be noted that the images need only have at least two images at the left and right end positions that have moved the most. The shooting timing may be set, or a large number of images may be generated using a high-speed shirt. However, as will be described later, when generating an edge image, it is preferable to generate a plurality of images because there are more distinct edge images when there are a plurality of images between the left and right ends. This area may be appropriately adjusted according to the processing capability of the image processing unit 3 and the required three-dimensional shape detection speed. The image processing unit 3 may be an electronic computer such as a personal computer, but may be realized by a dedicated chip such as a DSP.

[0025] The visual axis fine movement device 4 is not limited to these, as long as it can vibrate the optical axis of the camera unit 10 in a predetermined direction. Specific examples include using a piezoelectric element, a giant magnetostrictive element, an electrostatic actuator, a hydraulic actuator, a pneumatic actuator, an electromagnet, an optical actuator, a shape memory alloy, a high molecular weight actuator, and the like. Is possible.

[0026] Further, the visual axis fine movement device 4 may be a device that moves the camera unit 10 itself minutely, or may be a device that moves the lens 1 minutely. When the lens 1 is moved minutely, for example, the lens portion may be configured as shown in FIG. FIG. 2 is a schematic front view for explaining an example of the structure of the lens portion when the lens is moved slightly. As shown in the drawing, a visual axis fine movement device 4, for example, a piezoelectric element, more specifically, a piezoelectric ceramic is disposed around the lens 1, and the piezoelectric ceramic 4 is connected to the lens 1 by an appropriate member. The illustrated piezoelectric ceramic 4 is divided into four parts, and the lens 1 can be moved in any direction in the X-axis direction and the y-axis direction by controlling each part. However, if it is sufficient to move left and right, the piezoelectric ceramics need not be divided into four parts. The same configuration can be used when moving the camera unit 10 itself.

[0027] Referring again to FIG. 1, the relationship between the distance from the target object to the lens, the distance from the lens to the image sensor, and the amount of change in the imaging point on the image sensor as the optical axis of the camera unit 10 changes. Explain. As shown in the figure, if the distance from the target object 20 to the lens 1 is d, the distance from the lens 1 to the imaging element 2 is h, and the moving distance of the camera unit is 1, then the imaging point pi before moving the camera unit pi The distance s between and the image formation point P2 after movement is expressed by the following equation. s = hl / d (1)

[0028] From Equation 1, it can be seen that s increases as d decreases, and conversely, s decreases as d increases. That is, the shorter the distance from the lens to the target object, the larger the moving width s of the imaging point. Therefore, the distance to the target object is somewhat affected by the moving width s of the imaging point. That is, it can be said that the movement width s includes distance information to the object. Therefore, if you synthesize multiple images taken by moving the camera unit, multiple lines of nearby target objects with a large movement width s will be collected, and the lines of the target objects far away will have a movement width S. Because it is small, it must not be thick.

[0029] Generation of an edge image in the image processing unit 3 will be described with reference to FIG. Note that an edge image is an image in which an edge of a target object is emphasized in an image obtained by capturing the target object. Fig. 3 (a) is an edge image according to the prior art when the visual axis fine movement device is not used. For example, the edge is emphasized by differentiating the gray level difference of the sharply changing portion of the gray level in the image. No matter how many images of the target object are taken from the same position, the edge line width does not change. If the original edge has the same width, the line width is the same, and no information about the distance is included. .

However, the edge image obtained by processing the plurality of images of the camera unit force using the visual axis fine movement device according to the present invention by the image processing unit 3 is shown in FIG. 3 (b) according to the above-described movement width s. As shown, the near edges are thick and the far edges are thin. Therefore, it can be said that distance information is included in the edge width of this edge image, and the edges of the target object located at the same distance will have the same width. Will be located. FIG. 3 (b) is an edge image obtained when the optical axis of the camera unit is moved horizontally in the drawing, and the image is vertically moved in accordance with the movement width s described above. The edge of the direction is emphasized. In other words, the vertical edge contains distance information. The horizontal edge does not contain distance information. Therefore, if the edge is perfectly horizontal, the width of the edge will not increase, or it will not be displayed at all depending on the image processing that takes the difference.

[0031] The image processing in the image processing unit 3 is performed by differentiating the density difference of each image as described above. They may be overlapped, or the difference between the gray value and saturation value of the corresponding pixel of each image may be taken and normalized. Here, normalization means the process of moving the whole value in the positive direction or the force of taking the absolute value because the negative value is output when the difference between each image is taken. . Furthermore, the obtained image may be simplified by binarization. Further, if necessary, exaggeration processing or thin line key processing may be added. Image processing for generating such edge images includes conventional methods and all types of processing that can be developed in the future.

A configuration in the case where the camera unit configured as described above is used for detecting a three-dimensional shape will be described below. FIG. 4 is a schematic block diagram for explaining the configuration of the three-dimensional shape detection apparatus of the present invention. As shown in the figure, the camera unit 10 is arranged parallel to the left and right, and the respective outputs are input to the image processing unit 3. In this specification, the term “line of sight” means a line connecting the camera unit 10 and the target object 20, and the term “optical axis” means the optical center axis of the camera unit 10. And

[0033] In the following, as shown in Fig. 4, the power that mainly describes an example in which the camera unit 10 is arranged at two predetermined positions and the position force target object 20 with a different line of sight is photographed. It is not limited, and it may be configured such that one camera unit 10 is moved largely to the right and left to a predetermined shooting position, and shooting is performed at two places with different lines of sight. In this case, although not limited to this, for example, a moving mechanism that mounts the camera unit 10 on a rail or the like and enables movement on the rail may be provided. Furthermore, the shooting position is not limited to two places. If it is a binocular type, it is sufficient to have two locations. However, if it is desired to detect the surface shape of a three-dimensional object more precisely and with high accuracy, it may be possible to arrange camera units at multiple locations. That is, the camera units 10 can be arranged not only in the X-axis direction but also in the y-axis direction. Note that, from the viewpoint of ease of processing and the like, it is preferable that the imaging elements of each camera are arranged on the same plane.

In the camera unit 10 arranged in this way, the visual axis fine movement device 4 slightly moves the optical axis of the camera unit in a direction connecting two predetermined photographing positions. The minute movement may be a translational movement in the normal direction of the optical axis of the camera unit 10. Further, it may be a rotational motion that is not just a translational motion. In the case of rotational movement, the center of rotation is other than the optical center of the lens. Yes, it is preferably on or near the optical axis. That is, any movement is possible as long as the optical axis of the camera unit 10 changes. For example, since the human eyeball is finely moved by the rotational movement, when the solid shape detection device of the present invention is applied to the humanoid robot, the visual actuator or the like that causes the normal eye movement is viewed as it is. It can also be used as a shaft fine movement device. From the viewpoint of ease of processing, etc., the rotation centers of the cameras are preferably arranged on the same plane. In addition, the rotation angle of the camera unit is preferably adjusted so that the movement width s of the target object close to infinity on the image sensor is about 0 to 3 pixels. As a result, the edge of a target object that is close to infinity is as thin as possible (for example, the width of two pixels) or is not captured at all.

[0035] Thus, in this specification, "movement in the direction connecting two predetermined imaging positions" refers to a camera unit (lens) that is not limited to translational motion in the normal direction of the optical axis of the camera unit. It also includes rotational movements around a given point in the direction in which they approach or move away from each other.

[0036] The moving direction of the visual axis fine movement device 4 according to the present invention will be described with reference to FIG. FIG. 5 is a diagram for explaining an example in which the optical axes of a plurality of camera units 10 are moved in a direction connecting them, and is a schematic front view of the camera units in which the front force is also viewed. FIG. 5 (a) shows an example in which there are two camera units, and the visual axis fine movement device finely moves the camera units 10a and 10b to the left and right in the direction of ab. If there are three camera parts, for example, as shown in Fig. 5 (b), the camera part should be placed at the apex of the triangle, and the camera parts 10a and 10b will move finely in the direction ab during shooting. Switch the shooting position and move it slightly in the direction of ac during shooting with the camera units 10a and 10c. Furthermore, the shooting position is switched so that the camera unit 10b and 10c can be moved slightly in the direction of be during shooting. Thus, by finely moving the optical axis of the camera unit in a plurality of directions, it becomes possible to more accurately detect the distance between the edges in the plurality of directions. Furthermore, as shown in FIG. 5 (c), it is of course possible to make fine movements up and down and left and right using the four camera units 10a to LOd. In the three-dimensional shape detection apparatus according to the present invention, since the optical axis only needs to be moved in the direction connecting the shooting positions, the three-dimensional shape detection apparatus is finely moved in a plurality of directions as shown in FIG. 5 (b) and FIG. 5 (c). Of course, it doesn't matter.

[0037] Further, the optical axis may be slightly moved in a direction other than the direction connecting the camera units shown in FIG. Of course it doesn't matter. By finely moving the optical axis in multiple directions, it is possible to perform movements corresponding to tremor drift movements other than microsaccades, such as human eyeball movements, and complement the edge image.

[0038] When a plurality of camera units are used, it is preferable to synchronize the camera units. In other words, the minute movement of each camera unit is the same movement, and at the same time, the camera unit is configured to move in the same direction with the same width and the same minute movement. Also, photographing is performed at the same time. This makes it possible to obtain a good edge image even for a moving target object.

A method for associating the reference points of each edge image using the edge image obtained in this way will be described below. In general, the non-turn matching method is used to obtain the corresponding points of images taken using two camera units. Of course, the pattern matching method can also be used in the present invention. Further, for example, the edge image can be simplified to enable high-speed processing by the method described below.

FIG. 6 is a view for explaining each edge image obtained when a target object is imaged using two camera units having the visual axis fine movement device according to the present invention. Since the optical axis of the camera unit is finely moved left and right by the visual axis fine movement device, the force that generates an image with emphasized vertical edges is further simplified, and only the vertical edges are extracted. The result of image processing is shown in the figure. As described above, since the edge of the edge image according to the present invention includes distance information, those at the same distance become edges having the same width. Therefore, the edge width and the edge length are the same. Based on this, the edges of the edge images from the two camera units can be associated. That is, for the edges Ra, Rb, Rc of the left edge image in FIG. 6 and the edges La, Lb, Lc of the right edge image, for example, the edge corresponding to the edge Rb of the left edge image is selected from the right edge image column. When determining, an edge having the same edge width and length as the edge width and length of the edge Rb is detected from the right edge image. Then, an edge Lb having the same width and the same length is detected. Therefore, it is possible to associate the left and right edge images with the upper left vertex of these edges Rb and Lb as a reference point.

[0041] When the edge width and length of the edge image are not constant in a complicated shape, the pattern to be matched is found by finding similar patterns in the left and right images. Use the matching method.

[0042] Then, by obtaining the parallax using the edge image in which the reference points are associated, it is possible to detect the three-dimensional shape.

[0043] Thus, according to the present invention, the edge image can be very simple, and the reference points can be associated simply by using the edge length and width of the edge image as a reference. It is possible to greatly reduce the processing time required. If necessary, edge images with two or more shooting position forces can be added to make it possible to detect more detailed and three-dimensional shapes. Furthermore, after constructing a stereoscopic image, the smooth surface shape of the target object in the part surrounded by the edge is obtained by analyzing, for example, the gray value, and pasted to the stereoscopic image as stereoscopic information on the surface of the target object. Is also possible.

[0044] Note that if the target object is located near the central axis between the left and right camera units, the edge image force obtained as described above can also be associated, but the target object is between the left and right camera units. If the center axial force of the is at a position that is greatly deviated, the distance from each camera section will change greatly even at the same edge, and the width of the edge may change even though it is a corresponding edge. In such a case, the direction of the line of sight to the target object may be detected in addition to the reference. For example, in the left edge image, the direction of the line of sight is divided by measuring how far the edge is from the center of the edge image. It is possible to associate edges with the same length from among the existing edges. Furthermore, it is also possible to convert each edge of the obtained edge image into a predetermined reference width based on the direction of the line of sight to the target object. In other words, by converting the direction of the line of sight that is shifted to the width (reference width) when moved on the optical axis, it is possible to simply compare the width and length of the edge without considering the direction of the line of sight. It is also possible to make it possible.

It should be noted that the three-dimensional shape detection apparatus and the three-dimensional shape detection method of the present invention are not limited to the illustrated examples described above, and can be variously modified without departing from the scope of the present invention. It is.

Brief Description of Drawings

FIG. 1 is a diagram for explaining details of a camera unit used in the three-dimensional shape detection apparatus of the present invention. FIG.

FIG. 2 is a schematic front view for explaining the visual axis fine movement device of the lens unit when the lens is moved minutely.

[FIG. 3] FIG. 3 is a diagram for explaining an edge image. FIG. 3 (a) shows an edge image when the visual axis fine movement apparatus is used, and FIG. 3 (b) shows a visual axis fine movement apparatus. Edge image when used

FIG. 4 is a schematic block diagram for explaining the configuration of the three-dimensional shape detection apparatus of the present invention.

FIG. 5 is a schematic front view of the camera unit for explaining an example in which the optical axes of a plurality of camera units are moved in a direction connecting the camera units.

FIG. 6 is a diagram for explaining each edge image obtained when a target object is photographed using two camera units having the visual axis fine movement device according to the present invention.

Explanation of symbols

1 lens

2 Image sensor

3 Image processing section

4 Visual axis fine movement device

10 Camera

20 Target object

Claims

The scope of the claims

[1] A three-dimensional shape detection apparatus for photographing a target object and detecting the three-dimensional shape, the apparatus comprising:

At least one camera means having an image sensor and a lens for photographing the target object from at least two predetermined photographing positions having different lines of sight to the target object;

Visual axis fine movement means for slightly moving the optical axis of the camera means in a direction connecting the at least two predetermined photographing positions;

Image processing is performed on a plurality of images of the camera unit force whose optical axis is slightly moved by the visual axis fine moving unit, thereby obtaining edge images obtained by extracting the edges of the target object at the at least two predetermined photographing positions. Image processing means for generating and detecting corresponding edges of the target object by comparing the respective edge images;

A three-dimensional shape detection apparatus comprising:

[2] In the three-dimensional shape detection device according to claim 1, the predetermined imaging position is arranged along at least one of a horizontal direction, a vertical direction, an oblique direction, or a plurality of these directions. A three-dimensional shape detecting device characterized by the above.

[3] The three-dimensional shape detection apparatus according to claim 1 or 2, further comprising a moving unit capable of moving the camera device to a predetermined photographing position. apparatus.

[4] The three-dimensional shape detection apparatus according to claim 1 or 2, wherein the camera means has at least two camera forces, and each camera is arranged in advance at a predetermined photographing position. Shape detection device.

[5] The three-dimensional shape detection device according to claim 4, wherein the at least two camera units are synchronized with each other and simultaneously photograph with the same minute movement.

6. The three-dimensional shape detection apparatus according to any one of claims 1 to 5, wherein the visual axis fine movement means slightly moves the lens.

[7] The three-dimensional shape detection apparatus according to any one of claims 1 to 5, wherein the visual axis fine movement means slightly moves the camera means. Place.

[8] The three-dimensional shape detection device according to any one of claims 1 to 7, wherein the visual axis fine movement means includes a piezoelectric element, a giant magnetostrictive element, an electrostatic actuator, a hydraulic actuator, a pneumatic actuator, an electromagnet, and light. A three-dimensional shape detection device comprising any one of an actuator, a shape memory alloy, and a polymer actuator.

[9] In the three-dimensional shape detection device according to any one of claims 1 to 8, the fine movement by the visual axis fine movement means is a translational movement in a normal direction of the optical axis of the camera means. A featured three-dimensional shape detection apparatus.

[10] The three-dimensional shape detection apparatus according to any one of [1] to [8], wherein the fine movement by the visual axis fine movement means is a rotational movement about a predetermined point. Detection device.

[11] The three-dimensional shape detection apparatus according to claim 10, wherein the rotational angle of the rotational motion is such that the movement width of the target object close to infinite on the image sensor is 0 to 3 pixels wide. A three-dimensional shape detection apparatus characterized by being an angle.

[12] A three-dimensional shape detection method for photographing a target object and detecting the three-dimensional shape, the method comprising:

The process of photographing the target object with at least one camera means having an image sensor and a lens from at least two predetermined photographing positions having different lines of sight to the target object;

A step of slightly moving the optical axis of the camera means in a direction connecting the at least two predetermined photographing positions during the photographing step;

A process of generating edge images in which edges of the target object are extracted at the at least two predetermined photographing positions by performing image processing on a plurality of images from the camera unit in which the optical axis is moved minutely;

Detecting the corresponding edge of the target object by comparing the respective edge images;

A three-dimensional shape detection method comprising:

[13] The three-dimensional shape detection method according to claim 12, wherein the step of generating the edge image includes performing a difference process on a gray value or a saturation value of each corresponding pixel of the plurality of images to perform normalization. A three-dimensional shape detection method characterized by performing.

14. The three-dimensional shape detection method according to claim 13, wherein the step of generating the edge image further performs binarization processing.

[15] The solid shape detection method according to any one of claims 12 to 14, wherein the step of detecting the corresponding edge includes at least the width and length of the edge of the edge image. A three-dimensional shape detection method, comprising associating edges of an edge image at two predetermined photographing positions.

[16] In the three-dimensional shape detection method according to any one of claims 12 to 14, the process of detecting the corresponding edge may be performed by using a pattern matching method to detect an edge image at the at least two predetermined photographing positions. A solid shape detection method characterized by associating edges.

[17] The solid shape detection method according to any one of claims 12 to 16, wherein the step of detecting the corresponding edge further uses the direction of the line of sight to the target object as a reference. 3D shape detection method.

[18] In the three-dimensional shape detection method according to claim 17, in the process of detecting the corresponding edge, the edge of the generated edge image is converted into a predetermined reference width based on the direction of the line of sight to the target object. Then, the three-dimensional shape detection method characterized by comparing the respective edge images.