JP2000082141A - Picked up image geometric distortion detection device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect a large amount of misalignment even when an amount of misalignment of plural small compensation object areas dividing a picture is detected by arranging a temperature in a compensation object area which divides a reference picture or an inspection object picture into plural and making the template larger than the compensation object area. SOLUTION: A real template setting means 6 reads reference picture data 2 and generates a template 1 of data in a specific area of the reference picture data 2. The temperature 1 is usually a compensation object area obtained by dividing the reference picture data 2 into a rectangular small area but, in this case, the template 1 is provided in an area larger than the object compensation object area. Thus, it is possible to detect an amount of misalignment needed to compensate geometric distortion and it is possible to detect a large amount of even when a small amount of misalignment dividing the picture into plural is detected.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an inspection apparatus for comparing a reference image and an image to be inspected, in which a geometrical distortion of a captured image between the reference image and the image to be inspected is corrected and then the comparison is performed. Therefore, it belongs to the field of technology for detecting geometric distortion of a captured image. In particular, the present invention relates to a captured image geometric distortion detection device capable of detecting a large displacement amount even when detecting a displacement amount of a small correction target area obtained by dividing an image into a plurality of regions.

[0002]

2. Description of the Related Art For example, Japanese Patent Publication No.
The image data read from the pattern of the running printed matter at the time when the normal printed matter is printed is stored in the image memory as reference image data, and the reference image data read from the image memory is read from the printed matter to be inspected during printing. A technique relating to an inspection apparatus of a type in which the quality of a printed matter is determined by comparing the read inspection image data with a pixel unit is described.

As described above, when the reference image data and the inspection target image data are compared on a pixel-by-pixel basis, if the accuracy of defect detection is increased, even if the positional deviation between the two data is slight, the positional deviation is erroneously detected as defective. In order to prevent erroneous detection of a position shift as a defect, it is necessary to lower the accuracy of the defect detection. Therefore, if a certain amount of displacement cannot be avoided, inspection performance sufficient to satisfy the requirements cannot be obtained. Therefore, for example, Japanese Patent Application Laid-Open No. 7-249122 describes an inspection apparatus configured to correct a positional shift between reference image data and inspection target image data, and then compare and inspect the two data. I have.

[0004]

The inspection apparatus can correct a position shift with respect to a parallel movement of the entire image. However, when sudden tension fluctuations, meandering, vibration of the imaging camera, and the like of the web to be printed and transferred occur, the image obtained by imaging is not only a simple translational displacement but also a translational translation. , Stretch, skew, and,
It has projective distortion and other geometric distortions (see FIG. 8). This geometric distortion is particularly remarkable when printing is performed on a soft packaging film, building material decorative paper, or the like. This geometric distortion cannot be dealt with by the conventional displacement correction for the parallel movement. When detecting geometric distortion, an image is divided into a plurality of small regions, and a template region and a search region for detecting a movement vector (amount of displacement) are set for each of the small regions. However, an erroneous movement vector may be detected unless the template and the search range are reduced as the small area is made finer. Therefore, it is difficult to detect a large displacement.

Accordingly, an object of the present invention is to detect the amount of distortion required for correcting geometric distortion and to detect the amount of displacement of a plurality of small correction target areas obtained by dividing an image. It is an object of the present invention to provide a captured image geometric distortion detection device capable of detecting a large positional deviation amount even when the image is detected.

[0006]

The above objects are achieved by the present invention described below. In other words, the captured image geometric distortion detection apparatus according to the first embodiment of the present invention captures the web by combining main scanning by a line sensor camera and sub-scanning by transporting the web, and obtains a reference image for image inspection. And an inspection target image, the captured image expansion / contraction distortion detection device having a template matching unit that detects a positional shift amount between the reference image and the inspection target image using a template, wherein the template is the reference image or the inspection target. The image is arranged in a correction target area obtained by dividing the image into a plurality of parts, and the template is larger than the correction target area.

According to the present invention, the template is arranged in the correction target area obtained by dividing the reference image and the inspection target image into a plurality of parts, and a template larger than the correction target area is used. Therefore, a large amount of positional deviation is detected even when detecting the amount of positional deviation required for correcting geometric distortion and detecting the amount of positional deviation of a small correction target area obtained by dividing an image into a plurality. There is provided an apparatus for detecting a geometric distortion of a captured image.

According to a second aspect of the present invention, there is provided the captured image geometric distortion detecting apparatus according to the first aspect, wherein the template matching means is suitable for a matching operation in the area of the template. Real template setting means for setting a detailed position of an actual template to be actually used; top-and-bottom direction displacement amount detecting means for detecting a top-to-bottom position displacement amount; and left and right direction displacement amount detection for detecting a left and right direction displacement amount And an omnidirectional position shift amount detecting means for detecting an omnidirectional position shift amount.

According to the present invention, the template matching means comprises actual template setting means, top-bottom direction displacement amount detection means, left-right direction displacement amount detection means, and omnidirectional position displacement amount detection means. The detailed position of the actual template that is suitable for the matching calculation and is actually used in the template area is set by the template setting means, and the vertical position shift amount detecting means detects the vertical position shift amount, and the horizontal direction position shift amount detecting means , The amount of displacement in the left-right direction is detected, and the amount of displacement in all directions is detected by the omnidirectional displacement amount detecting means. That is, using the real template suitable for the matching calculation, the displacements in the top-to-bottom direction and the left-right direction are separately calculated, and finally, the omnidirectional displacements in only the vicinity of the top-bottom direction and the left-right displacement are calculated. Calculate. Therefore, the amount of displacement can be calculated at high speed with good accuracy.

According to a third aspect of the present invention, there is provided a captured image geometric distortion detecting apparatus according to the first or second aspect, wherein the template has an intersection portion substantially at the center of the correction target area. It has a cross shape of one pixel. That is, a template larger than the correction target area is used, and the number of pixels to be calculated can be reduced as compared with a rectangle or the like. Therefore, the amount of displacement can be calculated at high speed with good accuracy.

[0011]

Next, the present invention will be described with reference to embodiments. FIG. 1 is a diagram showing a configuration of a captured image composite distortion detection device of the present invention. In FIG. 1, 1 is template data, 2 is reference image data, 3 is inspection target image data, and 4 is displacement amount data. These data are generally stored in the storage unit, and are read from the storage unit and written to the storage unit as needed. Of course, for the inspection target image data 3, data obtained by imaging can be directly introduced into a processing means such as a pipeline processing method and used without using a storage means. Reference numeral 5 denotes a template matching unit. The template matching unit 5 is further composed of details, 6 is an actual template setting unit, 7 is a vertical direction positional deviation amount detecting unit, 8 is a horizontal positional deviation amount detecting unit,
Reference numeral 9 denotes an omnidirectional positional deviation amount detecting means.

The template data 1 is data of a specific area in the image data. Although the image data is not limited to this, usually, reference image data is used. FIG. 2 is a diagram illustrating an example of the template. In FIG. 2, reference numeral 2 denotes image data (reference image data) represented by an image, and R _{0000 to} R ₀₉₁₁ denote correction target regions obtained by dividing the reference image data 2 into small rectangular regions, and T ₀₁₀₁ and T _0110. , T _{18 01,} T ₀₈₁₀ is their correction target region template provided in a region larger than (rectangular portion indicated by hatching). The template data 1 is composed of a plurality of templates. In the example shown in FIG. 2, four templates T _{0101 to} T ₀₈₁₀ (template T
₀₁₀₁ , T ₀₁₁₀ , T ₁₈₀₁ , T ₀₈₁₀ ). FIG.
In the above, the templates T _{0101 to} T ₀₈₁₀ are rectangular, but are not limited to rectangles, and can be of any shape. However, in the present invention, even when the templates T _{0101 to} T ₀₈₁₀ have an arbitrary shape,
Enclosing rectangle of arbitrary shape, than the size of the rectangular region to be corrected R ₀₀₀₀ to R ₀₉₁₁ shown separated by line segments in FIG. 2, the larger size. In the subscripts of R ₀₉₁₁ , T _0810, etc., the first two digits represent the row number, and the last two digits represent the column number. The arrow → indicates the direction of web transport.

As shown in FIG. 2, a template T _0101-
T ₀₈₁₀ is arranged two-dimensionally in the top and bottom left and right directions with respect to the reference image and the inspection target image. Image data 2
Is composed of a plurality of pixel data arranged in a matrix, and each of the templates T _{0101 to} T ₀₈₁₀ is also composed of a plurality of pixel data arranged in a matrix. Then, a horizontal pixel column or a vertical pixel column as a set of a series of pixels in a row or a column can be formed.
_[0101] Each of _T10108 includes a horizontal pixel row and a vertical pixel row as elements.

As described above, the template is a template.
To T₀₁₀₁~ T₀₈₁₀Is not limited to a rectangle like
No. As an example, a rectangular template and a cross-shaped template
A comparison of the plates is shown in FIG. FIG. 3A shows a rectangular shape.
FIG. 3B shows a template having a cross shape.
Indicates a port number. In FIG. 3, R₀₀₀₁, R₀₁₀₀, R₀₂₀₁,
R₀₄₀₅, R₀₅₀₅, R₀₆₀₅Is the correction target area, T₀₁₀₁Is a rectangle
Template, T ₀₅₀₅Is a cross-shaped template
is there. A small rectangle drawn by a grid of thin line segments
The pixel of image data 2 is shown.
The rectangle drawn in the figure indicates the correction target area. Shown in FIG.
As described above, in this example, one correction target area is 25 (5
(Row x 5 columns).

In the example shown in FIG. 3A, the rectangular template T ₀₁₀₁ is set to include a correction target region R ₀₁₀₁ (not shown) composed of pixels of 5 rows × 5 columns. , 7 rows × 7 columns. Therefore, there are seven pixels in a horizontal pixel column as a set of a series of pixels in a row, and there are seven pixel columns. Also, seven pixels exist in a vertical pixel column as a set of a series of pixels in the column, and there are seven pixel columns.

On the other hand, in the example shown in FIG. 3B, the cross-shaped template T ₀₅₀₅ has 11 pixels in the horizontal pixel row, but has only one pixel row. Also, there are 11 pixels in the vertical pixel row, but there is only one pixel row. The cross-shaped template T ₀₅₀₅ has one horizontal pixel row and one vertical pixel row.
_If the intersection of ₀₅₀₅ may be an arbitrary place inside the correction target region R ₀₅₀₅ , there are substantially a plurality of horizontal pixel columns and a plurality of vertical pixel columns. Therefore, the rectangular template T ₀₁₀₁ and the cross-shaped template T ₀₅₀₅ can perform basically the same matching calculation (details will be described later).

When the geometric distortion of the captured image is local,
The geometric distortion cannot be detected by a single or a small number of templates. Therefore, it is necessary to divide the image into a large number of partial areas, each of which is used as a correction target area, and arrange a template in each of the areas to detect a positional shift amount (motion vector). If the amount of displacement is extremely different locally, it may be necessary to determine the amount of displacement for each pixel. When the template for calculating the displacement amount is the same as the correction target area or a partial area of the correction target area, the correction target area is reduced in order to prevent inconvenience such as erroneous detection. , The search range must be reduced. However, when the search range is reduced, a large displacement cannot be detected. As shown in FIG. 3, in the present invention, the search range is widened by making the template larger than the correction target area, so that a large displacement can be detected.

The feature of using a cross-shaped template such as the template T ₀₅₀₅ shown in FIG. 3 is remarkable in a case where the correction target area is made small and the amount of displacement is obtained for each pixel. That is, in such a case, a part of the calculation process can be omitted in the matching calculation described later. Due to the omission, the matching operation can be performed at high speed even if there are many templates. The calculation process that can be omitted is a vertical displacement detection process by the vertical displacement detection means 7 (step S5).
1) and a left-right direction displacement amount detection process by the left-right direction displacement amount detection means 8 (step S52). By omitting these, it is possible to proceed to the omnidirectional positional deviation amount detecting process (step S53) by the omnidirectional positional deviation amount detecting means 9. The reason for this is that in the cross-shaped template, it can be considered that the pixel row in the vertical direction (vertical pixel row) and the pixel row in the horizontal direction (horizontal pixel row) have already been selected, and the correction target area is small. This is because the range in which the intersection of the cross-shaped template is displaced is small.

Next, the matching operation will be described.
An example in which the four rectangular templates T _{0101 to} T ₀₈₁₀ shown in FIG. 1 are provided will be described. As described above, the present invention reduces the correction target area and provides a large number of templates that are not necessarily rectangular. It is particularly suitable for application to The real template setting means 6 shown in FIG. 1 first reads the reference image data 2 and generates template data 1 which is data of a specific area in the reference image data 2. That is, each of the above-described templates T _{0101 to} T ₀₈₁₀ is generated. Furthermore, the actual template setting unit 6 sets the detailed position of the actual template used actually suitable for matching operation in the area of the template T ₀₁₀₁ ~T _{08 10.} FIG. 4 is a diagram illustrating an example of a real template suitable for a matching operation. In the example shown in FIG. 4, the actual template is shown by a vertical pixel row, which is a set of pixels arranged in the vertical direction. Using the actual template indicated by the vertical pixel row, the template matching means 5 calculates the amount of displacement in the vertical direction.

As shown in FIG. 4, a vertical pixel row a is a pixel row passing substantially at the center of a rectangular pattern. By detecting the position of the edge in the left-right direction of this rectangular pattern, the amount of displacement in the vertical direction can be calculated.
This rectangular pattern has left and right edges whose position in the top and bottom directions does not change due to displacement in the left and right directions. Therefore, the vertical pixel row a is a real template suitable for the matching calculation for calculating the amount of displacement in the vertical direction. On the other hand, the vertical pixel row b is a pixel row passing near the right edge of the rectangular pattern. In the case of this pixel row, the right edge of the rectangular pattern is included in the positional shift in the left-right direction. May not be included. Therefore, it is not suitable for the matching calculation for calculating the amount of displacement in the vertical direction, and the actual template setting means 6 does not use the vertical pixel row b as the actual template.

The vertical pixel row c passes through substantially the center of the pattern having an inclined edge. The position of the inclined edge through which the vertical pixel row c passes in response to the positional shift in the left-right direction changes in the vertical direction. Therefore, it is not suitable for the matching calculation for calculating the amount of displacement in the vertical direction, and the actual template setting means 6 does not use the vertical pixel row c as the actual template. The vertical pixel row d is a pixel row passing through a rectangular pattern arranged at almost equal intervals in the vertical direction. The position of the edge of the rectangular pattern through which the vertical pixel row d passes with respect to the positional shift in the left-right direction does not change in the vertical direction. However, when a displacement in the vertical direction equal to or an integral multiple of the array interval occurs, there is a possibility that the misalignment calculation is erroneously performed at the same or an integral multiple of the array interval. Therefore, it is not suitable for the matching calculation for calculating the amount of displacement in the vertical direction, and the actual template setting means 6 does not use the vertical pixel row d as the actual template.

As described above, the actual template setting means 6
In the case of setting an actual template for detecting a displacement in the vertical direction, the evaluation value (described later) of the degree of coincidence in the matching calculation greatly changes with respect to the displacement in the vertical direction, and the displacement in the horizontal direction is large. , A vertical pixel row having a small change in the evaluation value of the matching degree in the matching calculation is set. In addition, a vertical pixel row in which a change in the evaluation value of the degree of coincidence in the matching operation with respect to the displacement in the vertical direction has a periodicity is avoided. In the above description, the setting of the real template for detecting the displacement in the vertical direction has been described. However, the same applies to the setting of the real template for detecting the displacement in the left-right direction, and the description thereof will be omitted. That is, the same applies if “top and bottom” is replaced with “left and right” and “vertical” is replaced with “horizontal”.

FIG. 5 is a flowchart showing an example of a process of selecting a pixel column to be set as an actual template. First,
In step S1, the contour strength of the template, which is a specific area in the reference image data, is calculated for the direction in which the displacement is to be corrected, and the number of pixels having a contour strength equal to or higher than a predetermined strength is calculated. The number of pixels is obtained by counting each of the pixel rows in the direction, and a pixel row having a predetermined number of pixels or more is a pixel row that can be selected as an actual template. As a result of this processing, a pixel row to be applied to the correction of the positional deviation between the reference image and the inspection image always includes the pixels of the contour part, and the contour has a predetermined strength. Therefore, a change in the evaluation value of the degree of coincidence is large, and an accurate correction amount of the positional deviation can be detected.

In the next step S2, one target pixel column among the plurality of pixel columns of the reference image in the direction in which the displacement is to be corrected, and a pixel column obtained by shifting the target pixel column by a predetermined pixel. , The absolute value of the difference for each pixel is calculated, and the absolute value of the difference is compared with the pixel value of the corresponding pixel of the contour image composed of the contour of the reference image. Since the absolute value of the difference has a pixel exceeding the pixel value of the pixel of the contour image, it is determined that the target pixel row is a pixel row whose picture is not only a repetitive component, and within each pixel row of the reference image, Such a pixel column is a selectable pixel column. By this processing, a pixel row including only a portion where the same picture repeats, that is, only a portion of the periodic picture, is not selected as a pixel row to be applied to the detection of the displacement correction value. Accordingly, there is no possibility that a correction value separated by a multiple of the repetition period is detected, and an accurate correction value of the positional deviation can be detected.

Next, in step S3, a target pixel row, which is one of the elements of a set of pixel rows belonging to the reference image in a direction parallel to the direction in which the displacement is corrected, For each of a plurality of adjacent pixel columns separated by a predetermined range in pixel units, a correction value of the positional deviation is detected from the evaluation value of the degree of coincidence when the positional relationship of the pixel columns is changed in the column direction. Then, the number of pixel rows for which the correction value is zero is obtained for the right and left directions of the target pixel row, and the smaller number is set as the frequency of the target pixel row. The frequency is determined using all the sets of the pixel rows belonging to the reference image as the target pixel rows, and the pixel row having the maximum or sufficiently large frequency is set as the selectable pixel row. By this processing, if the positional deviation is within the range of the frequency of the target pixel column or less, even if there is a positional deviation in a direction orthogonal to the direction of correcting the positional deviation, an appropriate positional deviation correction value can be detected. Can be.

Next, in step S4, the positional shift from the pixel row that is the selectable pixel row in step S1 described above, the selectable pixel row in step S2, and the selectable pixel row in step S3 is performed. A pixel row to be set as an actual template for applying the correction value to the detection is selected.
A plurality of pixel columns can be selected for a specific real template, and is not limited to one. For example, a plurality of adjacent pixel columns can be selected. The real template setting means 6 sets the real template in the top-to-bottom direction and the left-right direction for each of all the templates as described above. That is, in the example shown in FIG. 2, four real templates in the vertical direction and four real templates in the left-right direction are set for each of the four templates T _{0101 to} T ₀₈₁₀ .

The vertical position deviation amount detecting means 7 shown in FIG.
Reads the inspection target image data 3 and calculates the amount of displacement in the up-down direction using an actual template for detecting the displacement in the up-down direction. The top-bottom direction positional deviation amount detecting means 7 has the same position (the address of the read image data is the same) as the actual template which is the pixel row of the reference image data 2
The evaluation calculation is performed by shifting the pixel row of the inspection target image data 3 in the vertical direction while shifting the position in the vertical direction, and the evaluation value is obtained.

As the evaluation value of the coincidence, a correlation coefficient, a sum of absolute values of differences between corresponding pixels, a sum of squares of differences between corresponding pixels, and the like can be used. An evaluation value with a high degree of matching is
The correlation coefficient is a relative maximum, but the sum of the absolute value of the difference and the sum of the squares of the difference of the corresponding pixels is a relative minimum. Equation 1 below shows the equation for calculating the correlation coefficient, Equation 2 shows the equation for calculating the sum of the absolute values of the differences, and Equation 3 shows the equation for calculating the sum of the squares of the differences.

(Equation 1)

(Equation 2)

(Equation 3)

A lateral displacement detecting means 8 shown in FIG.
Reads the image data 3 to be inspected and calculates the amount of displacement in the left-right direction using an actual template for detecting the displacement in the left-right direction. The horizontal position shift amount detecting means 7 has the same position (the address of the read image data is the same) as the actual template which is the pixel row of the reference image data 2
The evaluation value is obtained by performing an evaluation operation on the pixel row of the inspection target image data 3 while shifting the position in the left-right direction, and the left-right positional shift amount is obtained based on the position of the evaluation value having the highest matching degree.

The omnidirectional displacement amount detecting means 9 shown in FIG. 1 reads the inspection target image data 3 and calculates the omnidirectional displacement amount using an actual template for detecting the omnidirectional displacement. The real template for detecting the misalignment in all directions is a combined pixel obtained by combining the real template for detecting the misalignment in the vertical direction described above and the real template for detecting the misalignment in the horizontal direction described above. Column. When the correction target area is small, the above-described cross-shaped template (see FIG. 3) can be regarded as a template similar to the united pixel row. The omnidirectional displacement amount detecting means 7 compares the actual template, which is the pixel row of the reference image data 2, with the pixel row of the inspection target image data 3,
An evaluation value is obtained by performing an evaluation operation while shifting the position in all directions (horizontal and vertical directions), and an omnidirectional positional shift amount is obtained from the position of the evaluation value having the highest degree of coincidence.

When the position is shifted in all directions (vertical and horizontal directions), the first position (center position) of the pixel row of the inspection target image data 3 is determined by the positional deviation obtained by the vertical positional deviation amount detecting means 7. The position in the vertical direction in which the amount has been corrected and the position in the horizontal direction in which the positional deviation obtained by the lateral positional deviation detecting means 8 have been corrected. An evaluation numerical value is obtained by performing an evaluation calculation while shifting the position from this position to a predetermined range (two-dimensional area), and a position shift amount in all directions (top and bottom right and left directions) is obtained from the position of the evaluation numerical value having the highest coincidence. By doing so, a united pixel row is used as an actual template, and a predetermined range can be narrowed (reduced), so that it is possible to accurately calculate the amount of displacement and to shorten the calculation time. .

The calculation of the above-mentioned positional deviation amount will be described in the order of calculation. FIG. 6 is a pictorial diagram showing a process of calculating the displacement amount. In the example shown in FIG. 6, the pictorial diagram shows that a plurality of adjacent pixel columns are selected for a specific real template. As described above, when a plurality of adjacent pixel columns are selected, the processing amount can be significantly reduced by narrowing the search range by using the positional deviation amounts sequentially obtained from one of the pixel columns as an initial value. Usually, since the change in the displacement amount is not large in adjacent pixel rows, no problem occurs even if the search range is narrowed.

First, in step S61 of FIG. 6, the vertical direction positional deviation amount detecting means 7 calculates the vertical direction positional deviation amount. Next, in step S62, the left / right positional deviation amount detection means 8 calculates the left / right positional deviation amount. Next, in step S63, the omnidirectional position shift amount calculating means 9 shifts the position in the predetermined direction from the position corrected in step S61 and step S62 for the position shift amount in the vertical and horizontal directions, and shifts the position to a predetermined range. (Right and left direction) Determine the amount of displacement. The omnidirectional (vertical left / right) positional deviation obtained by the omnidirectional positional deviation calculating means 9 is higher in accuracy than the vertical / horizontal positional deviation obtained in steps S61 and S62.

As described above, the top-to-bottom direction position shift amount detecting means 7, the left-right direction position shift amount detecting means 8, and the omnidirectional position shift amount calculating means 9 determine the position in all directions for all the templates. Calculate the shift amount. That is, in the example shown in FIG.
_[0101] For each of T ₀₈₁₀ to T ₀₈₁₀ , a total of eight positional shift amounts are calculated, two each for the vertical position shift amount and the horizontal position shift amount.

The plurality of displacement amounts can be calculated by directly introducing the inspection target image data 3 obtained by imaging into processing means such as a pipeline processing method without using storage means. . In that case, each template T
_[0101] For each of T101 to _T0810 , simultaneous parallel processing can be performed using a plurality of processors, and the processing speed can be increased.

Based on these eight displacements, (a) translation, (b) expansion and contraction, and
Distortions such as (c) skew, (d) projection, and (e) rotation can be detected. That is, four templates T
_{[0101] If the} amount of displacement in the vertical direction matches the amount of displacement in the horizontal direction for each of T101 to _T0810, the image data to be inspected moves in parallel with respect to the reference image data. (Having translation distortion).

Of the four templates, two of the templates T ₀₁₀₁ and T ₀₁₁₀ and the templates T ₀₈₀₁ and T ₀₈₀₁
For two of _0810, has a positional deviation amount spreading interval in the circumferential direction, while the two and the template T _0101, T _0110, the two templates T _0110, T _0810,
In the case where there is a positional shift amount in which the interval is narrowed in the left-right direction, the image data to be inspected expands in the up-down direction and contracts in the left-right direction with respect to the reference image data (has distortion in the up-down direction and left-right contraction). become. Further, of the four templates, two of the templates T ₀₁₀₁ and T ₀₁₁₀ and two of the templates T ₀₈₀₁ and T ₀₈₁₀ have positional shift amounts whose intervals are narrowed in the vertical direction.
_In the case where two of the templates T ₀₁₁₀ and T _{0801 and} the two templates T ₀₁₁₀ and T ₀₈₁₀ have positional deviation amounts that increase in the horizontal direction, the image data to be inspected with respect to the reference image data And expands in the left-right direction (shrinks up and down and has left-right elongation distortion).

Also, four templates T _{0101 to} T ₀₈₁₀
Are the same in the top and bottom directions, while the two templates T ₀₁₀₁ and T _{0110 and} the two templates T ₀₈₀₁ and T ₀₈₁₀ have different left and right displacements. In this case, the inspection target image data has skew distortion with respect to the reference image data. If the amount of displacement in the up-down direction and the amount of displacement in the left-right direction are different for each of the four templates T _{0101 to} T ₀₈₁₀ , the image data to be inspected is distorted relative to the reference image data. Will have.

Further, four templates T _{0101 to} T ₀₈₁₀
The position shift amount in the vertical direction and the position shift amount in the horizontal direction are both positive (or negative) for T ₀₁₀₁ in
A positional deviation amount in the circumferential direction about the T _{08 10,} when the positional deviation amount in the lateral direction are both a negative (or positive), the inspection target image data for the reference data is to have a rotational distortion .

If only the translational distortion of the image data to be inspected with respect to the reference image data is to be detected, at least one template is required. On the other hand, when detecting translational distortion, expansion / contraction distortion, skew distortion, and projection distortion of the inspection target image data with respect to the reference image data, at least four templates are required. Four templates T provided at four corners as shown in FIG.
_[0101] Not only _T1010 but also more templates can be used at arbitrary positions. In this case, operations such as judging the amount of misregistration except for an extreme value (for which erroneous detection was performed for some reason) and calculating an average value of the misregistration amounts are performed. be able to.
That is, the accuracy and reliability can be further improved by comprehensively evaluating the displacement amount. In addition, it is possible to cope with complex composite distortions that have undergone more complicated partial expansion and contraction.

FIG. 7 is a diagram showing an example in which the captured image composite distortion detecting apparatus of the present invention is applied to a printed matter inspection apparatus. 7, reference numeral 71 denotes a camera unit, 72 denotes a camera control unit, 73 denotes a main body of a printed matter inspection apparatus, 74 denotes an image data memory to be inspected, 75 denotes a reference image data memory, 76 denotes a reference input command input unit, and 77 denotes a composite distortion detection. Means, 78 is a composite distortion correction comparing unit, and 79 is a parameter input unit. Each of the reference image data memory 75 and the inspection target image data memory 74 has a storage capacity capable of storing at least one unit of a printed material (a print screen for one cycle performed by the printing unit).

The reference input command input unit 76 takes a reference image for starting the image inspection, inputs a command to the reference image data memory 75, and then takes a target image to be inspected and stores the target image data. Memory 7
Command to input to 4 is performed. This command switches the selector. When the input of the reference image data is commanded by the reference input command input unit 76, the selector of FIG. 2 connects the input of the imaging data to the reference image data memory 75,
At this time, the composite distortion detecting means 77 and the composite distortion correction comparing section 78 do not operate. On the other hand, when the input of the image data to be inspected is commanded by the reference input command input unit 76, the selector makes an input connection of the image data to the image data memory 74 for inspection.

The composite distortion detecting means 77 detects the translational distortion, the expansion / contraction distortion, the skew distortion, the composite distortion, or the amount of the positional deviation indicating the translational distortion between the inspection object image and the reference image. The correction amount of the composite distortion such as the expansion / contraction distortion, the skew distortion, the projection distortion, or the like, or the correction amount of the positional deviation amount indicating the same is sent to the distortion correction comparing unit 78. Then, the composite distortion correction comparing unit 78, which has received the composite distortion correction amount or the correction amount of the positional deviation amount indicating the same,
The inspection target image data and the reference image data are compared in consideration of the correction amount. Also, the parameter input unit 79
Composite distortion detecting means 77 and composite distortion correction comparing section 78
Input for setting the parameters used in.
As the parameter, for example, the projection distortion correction comparing unit 7
In step 8, a comparison is made between the image data to be inspected and the reference image data, and a threshold for judging pass / fail is input.

[0044]

As described above, according to the present invention, the amount of positional deviation required for correcting geometric distortion is detected, and the amount of positional deviation of a small correction target area obtained by dividing an image into a plurality of parts is detected. Provided is a captured image geometric distortion detection device capable of detecting a large positional deviation amount even in the case of performing detection. Further, according to the captured image geometric distortion detection device of the second aspect of the present invention, the real-time template suitable for the matching calculation is used to separately calculate the vertical and horizontal displacements. Since the directional displacement is calculated only in the vicinity of the displacement in the left and right directions, the displacement can be calculated at high speed with good accuracy.
Further, according to the captured image geometric distortion detection device of the third aspect of the present invention, a template larger than the correction target area is used, and the number of pixels to be calculated is reduced as compared with a rectangle or the like. Therefore, the amount of displacement can be calculated at high speed with good accuracy.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of a captured image composite distortion detection device of the present invention.

FIG. 2 is a diagram illustrating an example of a template.

FIG. 3 is a diagram showing a comparison between a rectangular template and a cross template.

FIG. 4 is a diagram showing an example of a real template suitable for a matching operation.

FIG. 5 is a flowchart illustrating an example of a process of selecting a pixel column to be set as an actual template.

FIG. 6 is a pictorial diagram showing a process of calculating a displacement amount.

FIG. 7 is a diagram showing an example in which the captured image composite distortion detection device of the present invention is applied to a printed matter inspection device.

FIG. 8 is a diagram illustrating each distortion of translation, expansion, contraction, skew, and projection.

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 template data 2 reference image data 3 inspection target image data 4 positional shift amount 5 template matching means 6 actual template setting means 7 vertical position shift amount detecting means 8 lateral position shift amount detecting means 9 omnidirectional position shift amount detecting means 61 Camera unit 62 Camera control unit 63 Printed matter inspection device main body 64 Inspection object image data memory 65 Reference image data memory 66 Reference input command input unit 67 Composite distortion detection means 68 Composite distortion correction comparison unit 69 Parameter input unit

Claims (3)

[Claims] An image of the web is taken by combining a main scan by a line sensor camera and a sub-scan by transporting the web, and a reference image for image inspection and an image to be inspected are obtained using a template. A captured image geometric distortion detection device having a template matching unit that detects a positional shift amount with respect to the inspection target image, wherein the template is arranged in a correction target region obtained by dividing the reference image or the inspection target image into a plurality of parts, The captured image geometric distortion detecting device is characterized in that the template is larger than the correction target area. 2. A captured image geometric distortion detecting apparatus according to claim 1, wherein said template matching means includes: a real template setting means for setting a detailed position of a real template to be used for matching operation and actually used within a region of the template; , A vertical position shift amount detecting means for detecting a vertical position shift amount, a horizontal position shift amount detecting means for detecting a horizontal position shift amount, and an omnidirectional position shift detecting an omnidirectional position shift amount. An amount detection means, comprising: a captured image geometric distortion detection device; 3. The captured image geometric distortion detecting apparatus according to claim 1, wherein the template has a cross-shaped shape in which an intersecting portion is substantially one pixel at the center of the correction target area. Strain detector.