Measurement system

Abstract

To reduce a harmful effect of foreign object adhesion to a lens and a lens cover of a camera.SOLUTION: An image space is divided into a plurality of evaluation object blocks; an absolute value of a difference in an image attribute value of each evaluation unit block between photographed images temporally adjacent to each other in a period of a prescribed time length T is obtained; the total sum of the obtained absolute values of the difference is set as an evaluation value EV of the evaluation unit block; the evaluation unit block in which the obtained evaluation value EV is not within a prescribed acceptance range is extracted as a defective block; the aggregation of the defective blocks is set as a defective region; a pixel value is used as the image attribute value of the evaluation unit block if the evaluation unit block is a region of one pixel; and an average value of the pixel value of each pixel in the region, a histogram in the region, a spectrum of a spatial frequency in the region and the like can be used if the evaluation unit block is the region of the plural pixels. A luminance value of the pixel may be used as the pixel value of the pixel.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present invention relates to a technique for performing measurement using an image captured by a camera.

Background Art

[0002] As a technique for performing measurement using an image captured by a camera, an area in an image captured at a time t2 after a time t1, which is similar to a feature area in the image captured at the first time t1, is searched by template matching, and the amount of movement from the feature area of the searched area is converted into the amount of movement in the real space, and a technique for calculating the relative amount of movement between the camera and the object is known (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When performing measurement using a camera in an unclean environment such as outdoors, if foreign substances such as water droplets or mud adhere to the lens or lens cover of the camera, the area in the captured image corresponding to the adhered range no longer represents the image of the object, and thus correct measurement may not be possible.

[0005] Therefore, an object of the present invention is to reduce the adverse effects of foreign matter adhesion to the lens or lens cover of a camera in measurement using the camera.

Means for Solving the Problems

[0006] To achieve the above object, the present invention provides a measurement system that performs measurement using a measurement unit that performs the measurement using a captured image of an object captured by a camera, divides an image space into a plurality of evaluation target blocks each composed of one or more pixels, and for each evaluation target block, uses a plurality of captured images selected from among the captured images during a period of a predetermined time length as evaluation target images, obtains the absolute value of the difference in the image attribute values of the evaluation unit blocks between temporally adjacent evaluation target images, and calculates the sum of the obtained absolute values of the differences as the evaluation value of the evaluation unit block. An evaluation value calculation means, and a defective area identification means for identifying a set of defective blocks as a defective area, which is an area unsuitable for use by the measurement means for measurement, when the evaluation value obtained by the evaluation value calculation means is not included in a predetermined pass range. The image attribute value of the evaluation unit block is a value determined by the pixel values of the respective pixels within the evaluation unit block.

[0007] In this measurement system, the pixel value of the pixel may be the luminance value of the pixel, the evaluation unit block may be an area composed of one pixel, and the image attribute value of the evaluation unit block may be the luminance value of one pixel included in the evaluation unit block of the evaluation target image. Alternatively, in the above measurement system, the pixel value of the pixel may be the luminance value of the pixel, the evaluation unit block may be an area composed of a plurality of pixels, and the image attribute value of the evaluation unit block may be any one of the average value of the luminance values of a plurality of pixels included in the evaluation unit block of the evaluation target image, the histogram of the luminance values, and the spectrum of the spatial frequency of the luminance values.

[0008] The above measurement system may set the pass range such that the sum does not include a value greater than or equal to a first predetermined value and does not include a sum less than a second predetermined value that is smaller than the first predetermined value. In the above measurement system, the evaluation value calculation means may calculate the evaluation value of the evaluation unit blocks within the group using a plurality of different captured images as evaluation target images for each group of one or more evaluation target blocks. An abnormality presenting means for presenting the occurrence of an abnormality may be provided to the above measurement system when the size of the defective area identified by the defective area identifying means is equal to or greater than a predetermined level. The above measurement system may be provided with a target area setting means for setting a target area in the captured image, a search means for searching for an area in the current captured image that matches the target area set by the target area setting means in the previous time as a tracking result area, and in each measurement, calculating a movement amount on the captured image from the target area set by the target area setting means in the previous time to the tracking result area searched by the search means in the current time, and converting the calculated movement amount on the captured image into a relative movement amount of the camera with respect to the object. The target area setting means may set the target area so as not to include the defective area set by the defective area identifying means.

[0009] In this case, the search means may exclude the defective area identified by the defective area setting means from the search target and perform the search for the tracking result area. Further, the target area setting means estimates, from the history of the calculated movement amount on the captured image, a predicted movement amount of the image in the next captured image with respect to the image in the current captured image, and sets the target area so that the area moved by the predicted movement amount does not include the defective area set by the defective area identifying means.

[0010] Also, in this case, the camera may be mounted on a moving body and photograph the traveling surface on which the moving body travels as the object. According to such a measurement system, in a defective area in a captured image in which the object cannot be normally photographed due to foreign matter adhesion to the lens or lens cover of the camera, by utilizing the fact that the temporal change of the pixel value shows an abnormal value, the defective area can be identified. Therefore, according to the identified defective area, appropriate measures can be taken to reduce the adverse effects caused by foreign matter adhesion.

Effect of the Invention

[0011] As described above, according to the present invention, in measurement using a camera, the adverse effects of foreign matter adhesion to the lens or lens cover of the camera can be reduced.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Embodiments for Carrying Out the Invention

[0013] The first embodiment of the present invention will be described. FIG. 1 shows the configuration of a movement amount measurement system according to the first embodiment. As shown in the figure, the movement amount measurement system includes a measurement device 1, a stereo camera 2, and an abnormality notification device 3. The measurement device 1 includes a target area setting unit 11, a tracking processing unit 12, a separation distance measurement unit 13, a defective area calculation unit 14, a movement vector calculation unit 15, an actual distance conversion coefficient calculation unit 16, and a movement state calculation unit 17. The stereo camera 2 includes two cameras, a first camera 21 and a second camera 22. The movement measurement system is a system that measures the relative movement amount between the object photographed by the stereo camera 2 and the stereo camera 2, and can be applied to the measurement of the movement amount as shown in FIGS. 2a and 2b, for example. FIG. 2a shows an application example in which the stereo camera 2 is fixed to a moving body (an automobile in the figure), and the movement amount of the moving body with respect to the road surface is measured with the road surface as the object. In this case, the stereo camera 2 is arranged such that the first camera 21 and the second camera 22 photograph the road surface from directly above. Further, the first camera 21 and the second camera 22 are spaced apart in a direction perpendicular to the main movement direction MD (the forward direction of the moving body) of the stereo camera 2 with respect to the object (road surface) and perpendicular to the optical axes of the first camera 21 and the second camera 22. Further, the first camera 21 and the second camera 22 are arranged such that the upward direction of the photographed image is the movement direction MD.

[0014] FIG. 2b shows an application example in which the stereo camera 2 is fixed to a reference coordinate system, and the movement amount of an object surface (the conveyance object placement surface of a belt conveyor in the figure) moving with respect to the reference coordinate system is measured with the object surface as the object. In this case, the stereo camera 2 is arranged such that the first camera 21 and the second camera 22 photograph the object surface from directly above. Further, the first camera 21 and the second camera 22 are spaced apart in a direction perpendicular to the main movement direction MD (the direction opposite to the movement direction with respect to the reference coordinate system of the object surface) of the stereo camera 2 with respect to the object (object surface) and perpendicular to the optical axes of the first camera 21 and the second camera 22. Further, the first camera 21 and the second camera 22 are arranged such that the upward direction of the photographed image is the movement direction MD.

[0015] Therefore, the first camera 21 and the second camera 22 are arranged side by side in the left - right direction of the image in the photographed image, the up - down direction of the photographed image is parallel to the movement direction MD, and the left - right direction of the photographed image is the direction perpendicular to the movement direction MD on the object. Returning to FIG. 1, the defect area calculation unit 14 performs a defect area calculation operation to calculate, as a defect area, an area on the images captured by the first camera 21 and the second camera 22 where an object cannot be properly captured due to the adhesion of foreign matters such as water droplets and mud to the lens or the lens cover. Details of the defect area calculation operation will be described later.

[0016] The defect area calculation unit 14 notifies the abnormality presentation device 3 of the defect area calculated by the defect area calculation operation. In addition, if there is no adhesion of foreign matters to the calculated defect area on the image captured by the first camera 21 and the calculated defect area on the image captured by the second camera 22, the defect area calculation unit 14 sets, as unusable areas, the part of the object that would be captured and the area on the image captured by the first camera 21 that would be captured if there were no adhesion of foreign matters in the calculated defect areas on the images captured by the first camera 21 and the second camera 22 in the following manner: to the target following area setting unit 11 and the tracking processing unit 12.

[0017] If the abnormality presentation device 3 is notified of a defect area from the defect area calculation unit 14, it stores the information on the notified defect area. Then, in response to an operator's operation, it presents the stored information on the defect area so that the operator can recognize it. This presentation is performed, for example, by display output of the information on the defect area or transfer of data representing the information on the defect area to the outside.

[0018] In addition, when the abnormality presentation device 3 is notified of a defect area from the defect area calculation unit 14, or when the total area of the notified defect areas exceeds a predetermined level, it outputs a warning that an abnormality has occurred. This warning output is performed, for example, by display output or voice output.

[0019] Next, the tracking operation performed by the target following area setting unit 11 and the tracking processing unit 12 of the measuring device 1 will be described. After the start of the measurement operation of the measuring device 1, the measurement operation is repeatedly executed intermittently. Here, as shown in FIG. 3a, let the start point of the measurement operation be represented by t = 1, and the execution point of the nth measurement operation from the start point of the process be represented by t = n. Also, let the image captured by the first camera 21 at t = n be represented by P(t = n). The target tracking area setting unit 11 sets a target tracking area A(t = i) of a fixed size in the image P(t = i) at each time point t = i (where i is an arbitrary integer of 1 or more). This setting is performed so that the target tracking area A(t = i) does not overlap with the unusable area notified from the defective area calculation unit 14. The tracking processing unit 12 searches by template matching processing for an area within the range excluding the unusable area notified from the defective area calculation unit 14 in the image P(t = i + 1) that contains the image most similar to the image of the target tracking area A(t = i) in the image P(t = i) at each time point t = i + 1, and sets it as the tracking result area B(t = i + 1). That is, the tracking processing unit 12 excludes the unusable area notified from the defective area calculation unit 14 from the search target and searches for the tracking result area B(t = i + 1).

[0020] Also, for the first target tracking area A(t = 1) at t = 1, as shown in Fig. 3b, the reference point Ag(t = 1), which is the pixel position at the lower left of the target tracking area A(t = 1), is included in the reference point allowable area Q(t = 1), which is a preset area in the image P(t = 1) captured by the first camera 21, and the target tracking area A(t = 1) is set so as not to overlap with the unusable area notified from the defective area calculation unit 14.

[0021] Next, as shown in Figs. 3c1 and c2, the tracking processing unit 12 searches for an area in the image P(t = i + 1) that contains the image most similar to the image of the target tracking area A(t = i) in the image P(t = i) at each time point t = i + 1, and sets it as the tracking result area B(t = i + 1), and calculates a movement vector VP(t = i + 1) in the image space with the reference point Ag(t = i) of the target tracking area A(t = i) as the starting point and the reference point Bg(t = i + 1), which is the pixel position at the lower left of the searched tracking result area B(t = i + 1), as the ending point.

[0022] For the trailing area A(t = i + 1) after the second time and later, if the reference point Bg(t = i + 1) of the tracking result area B(t = i + 1) searched at t = i + 1 is within the reference point allowable area Q(t = i + 1) as shown in Fig. 3d1, the tracking result area B(t = i + 1) is directly used as the trailing area A(t = i + 1). On the other hand, if the reference point Bg(t = i + 1) of the tracking result area B(t = i + 1) is not within the reference point allowable area Q(t = i + 1) as shown in Fig. 3d2, similar to the case when t = 1, the trailing area A(t = i + 1) is set so that the reference point Ag(t = i + 1) is included in the reference point allowable area Q(t = i + 1) and does not overlap with the unusable area notified by the unusable area calculation unit 14. However, even when the reference point Bg(t = i + 1) of the tracking result area B(t = i + 1) is within the reference point allowable area Q(t = i + 1), the trailing area A(t = i + 1) may be set in the same way as when t = 1.

[0023] The reference point allowable area Q(t = i + 1) is set according to the movement vector VP(t = i + 1) and the acceleration vector obtained from the history of the movement vector VP so that the image of the part of the object projected into the trailing area A(t = i + 1) where the reference point Ag(t = i + 1) is included in the reference point allowable area Q(t = i + 1) is guaranteed to be included in the image P(t = i + 2) at the next time t = i + 2.

[0024] Here, as described above, the trailing area setting unit 11 sets the trailing area A(t = i) so that the reference point Ag(t = i) is included in the reference point allowable area Q(t = i) and does not overlap with the unusable area notified by the unusable area calculation unit 14. However, after updating the reference point allowable area Q(t = i) so that the trailing area A(t = i) that overlaps with the unusable area notified by the unusable area calculation unit 14 is not set, the trailing area A(t = i) may be set so that the reference point Ag(t = i) is included in the reference point allowable area Q(t = i).

[0025] Further, when i > 1, the target following area setting unit 11 estimates, from the movement vector VP(t = i) and the history of the movement vectors VP calculated so far, the movement amount of the image in the next captured image, image P(t = i + 1), with respect to the image in the current captured image P(t = i) as the predicted movement amount, and may set the target following area A(t = i) so that the target following area A(t = i) after moving by the predicted movement amount does not include the unusable area notified from the defective area calculation unit 14.

[0026] Next, the calculation operation of the actual distance conversion coefficient performed by the separation distance measurement unit 13 and the actual distance conversion coefficient calculation unit 15 of the measuring device 1 will be described. At the time t = 1, the separation distance measurement unit 13 calculates the distance ZA(t = 1) in the optical axis direction from the first camera 21 and the second camera 22 of the stereo camera 2 at the position on the object reflected in the center of the target following area A(t = 1). Further, at each time t = i + 1, the distance ZA(t = i + 1) in the optical axis direction from the first camera 21 and the second camera 22 at the position on the object reflected in the center of the target following area A(t = i + 1), and the distance ZB(t = i + 1) in the optical axis direction from the first camera 21 and the second camera 22 at the position on the object reflected in the center of the tracking result area B(t = i + 1) are calculated.

[0027] The distance Z in the optical axis direction from the first camera 21 and the second camera 22 at the position on the object can be obtained as follows. Now, as shown in FIG. 4, let F [mm] be the focal length of the first camera 21 and the second camera 22 of the stereo camera 2, and M [mm] be the baseline length which is the distance in the real space between the first camera 21 and the second camera 22. Also, let Tg be the position on the object for measuring the distance Z [mm], c1 be the position in the left - right direction in the image space where the position Tg is captured by the first camera 21, and c2 be the position in the left - right direction in the image space where the position Tg is captured by the second camera 22. Further, let c11 be the position corresponding to c1 on the plane SF which is at a focal length F away from the first camera 21 in the optical axis direction, and c21 be the position corresponding to c2 on the plane SF which is at a focal length F away from the second camera 22 in the optical axis direction.

[0028] Also, let xl [mm] be the horizontal distance from the center position of the first camera 21 to c11, and xr [mm] be the horizontal distance from the center position of the second camera 22 to c22. And if p = xl - xr, then according to the principle of triangulation, the distance Z at the position Tg is Z = (M × F) / p which is obtained by. If the size of the area on the plane at a distance F from the first camera 21 projected onto one pixel of the first camera 21 is S [mm / pixel], then when the coordinates change by 1 in the image space of the first camera 21, the position of Tg changes by (Z / F) × S in the direction perpendicular to the distance Z. Therefore, using this relationship, the actual distance conversion coefficient calculation unit 15 calculates the actual distance conversion coefficient K(t = i + 1) from ZA(t = i) and ZB(t = i + 1) measured by the separation distance measurement unit 13 at each time point when t = i + 1. The actual distance conversion coefficient K(t = i + 1) takes the approximate Z(t = i + 1) as the average value {ZA(t = i) + ZB(t = i + 1)} / 2 of ZA(t = i) and ZB(t = i + 1), K(t = i + 1) = {Z(t = i + 1) / F} × S which is obtained by.

[0029] Next, the movement vector calculation unit 14 of the measurement device 1 uses the movement vector VP(t = i + 1) in the image space and the actual distance conversion coefficient K(t = i + 1) calculated by the actual distance conversion coefficient calculation unit 15 at each time point when t = i + 1 to calculate the relative movement vector V(t = i + 1) of the object with respect to the stereo camera 2 as V(t = i + 1) = K(t = i + 1) × VP(t = i + 1).

[0030] Then, the movement state calculation unit 16 of the measurement device 1 calculates and outputs various movement states such as the relative movement speed, acceleration, and movement direction of the object from the relative movement vector V(t = i + 1) of the object with respect to the stereo camera 2 calculated by the movement vector calculation unit 14 at each time point of t = i + 1. Further, the movement state calculation unit 16 may also calculate and output, as movement states, the relative angle of the object, etc. from the plurality of distances in the image calculated by the separation distance measurement unit 13.

[0031] Hereinafter, the defective area calculation operation performed by the defective area calculation unit 14 to calculate the defective area will be described. The calculation of the defective area in the image captured by the first camera 21 and the calculation of the defective area in the image captured by the second camera 22 in the defective area calculation operation are performed in the same manner. Therefore, hereinafter, the calculation of the defective area in the image captured by the first camera 21 will be described as a representative. In the defective area calculation operation, as shown in FIG. 5a, a plurality of regions obtained by dividing the image space of the image captured by the first camera 21 are set as evaluation unit blocks. The evaluation unit block may be a region of only one pixel, a two-dimensional region of a plurality of rows × a plurality of columns, or a one-dimensional region of one row × a plurality of columns or a plurality of rows × one column. Then, the evaluation of each evaluation unit block is performed using the images captured during the period of the predetermined time length T, and the process of calculating the defective area is repeated for each period of the time length T. That is, let w be a time length that is a natural number multiple of the frame period (time interval for outputting an image) of the first camera 21, let the time when the image is first captured during the period of the time length T be j + 0×w, let the time when the image is last captured during the period of the time length T be j + m×w, and let h be an integer from 0 to m. The extraction of defective blocks is performed by evaluating each evaluation unit block using the m + 1 images captured at the time j + h×w. In other words, the time length T is set to be m×w.

[0032] Hereinafter, the image captured at time j + h × w is represented as the image to be evaluated P(j + h × w). In the defective area calculation operation, as shown in FIG. 5b, for each evaluation unit block, while changing the integer R from 0 to m - 1, the absolute value of the difference in the image attribute values of the evaluation unit block between the image to be evaluated P(j + R × w) and the image to be evaluated P(j + (R + 1) × w) is obtained, and the sum thereof is calculated. That is, during a period of a predetermined time length T, the sum of the absolute values of the differences in the image attribute values of the evaluation unit block between temporally adjacent images to be evaluated P() is obtained.

[0033] Here, as the image attribute value of the evaluation unit block, if the evaluation unit block is a region of one pixel, the pixel value is used. If the evaluation unit block is a region of a plurality of pixels, the average value of the pixel values of each pixel in the region, the histogram in the region, the spectrum of the spatial frequency in the region, etc. can be used. Also, as the pixel value of the pixel, the luminance value of the pixel may be used.

[0034] Then, the sum of the obtained absolute values of the differences is set as the evaluation value EV of the evaluation unit block. Note that FIG. 5b shows how to obtain the evaluation value EV(B#1) for one evaluation unit block B#1, but actually, the evaluation value EV is obtained in the same way for other evaluation unit blocks other than B#1. Evaluation unit blocks for which the obtained evaluation value EV is not within a predetermined pass range are extracted as defective blocks, and the set of defective blocks is calculated as the defective area. When the evaluation unit block is a region corresponding to a range where an opaque foreign object such as mud adheres, the image of the evaluation unit block does not change, so the evaluation value EV of the evaluation unit block becomes a significantly small value. Also, when the evaluation unit block is a region corresponding to a range where a transparent foreign object with a changing shape such as a water droplet adheres, the image of the evaluation unit block changes rapidly, so the evaluation value EV of the evaluation unit block becomes a significantly large value.

[0035] In advance, set the range of the evaluation value EV excluding the significantly large range and the significantly small range that are presumably due to the attachment of foreign matter as the pass range. When the evaluation value EV exceeds the pass range or does not reach the pass range, set the evaluation unit block as a defective block. In the above defective area calculation operation, the evaluation value EV of all evaluation unit blocks is obtained during the time period T. However, each evaluation unit block is grouped for each one or more evaluation unit blocks, and the evaluation value EV of the evaluation unit blocks in different groups is obtained for each time period of the time period T so that the evaluation value EV of the evaluation unit blocks in each group is calculated in order. For example, as shown in FIG. 6, the evaluation value EV(B#1) of the evaluation unit block B#1 may be obtained during the first time period T, and the evaluation value EV(B#2) of the evaluation unit block B#2 may be obtained during the next time period T.

[0036] Alternatively, each evaluation unit block is grouped for each one or more evaluation unit blocks, w is set as a multiple of the frame period of the first camera 21, a part of the time period T for calculating the evaluation value EV of the evaluation unit blocks in different groups is temporally overlapped, and the evaluation target images P() for obtaining the evaluation value EV of the evaluation unit blocks in each group are set alternately in time to calculate the evaluation value EV of the evaluation unit blocks in each group. For example, as shown in FIG. 7, a part of the time period T(B#1) of the time period T for calculating the evaluation value EV(B#1) of the evaluation unit block B#1 and the time period T(B#2) of the time period T for calculating the evaluation value EV(B#2) of the evaluation unit block B#2 are temporally overlapped, and the evaluation target images P() for obtaining the evaluation values EV of the evaluation unit block B#1 and the evaluation unit block B#2 are set alternately in time to obtain the evaluation values EV(B#1) and EV(B#2).

[0037] The embodiments of the present invention have been described above. According to the present embodiment, by utilizing the fact that the temporal change of pixel values shows abnormal values in a defective region, which is a region in a captured image where a subject cannot be normally captured due to foreign matter adhesion to the lens or lens cover of a camera, the defective region is identified, and countermeasures are taken according to the identified defective region to reduce the adverse effects caused by foreign matter adhesion.

[0038] In addition, in the above embodiment, the distances ZA(t = i) and ZB(t = i + 1) calculated using the stereo camera 2 by the separation distance measurement unit 13 may be calculated using other devices such as a laser distance meter. Also, the roles of the first camera 21 and the second camera 22 in the embodiment may be exchanged.

[0039] The present invention can be similarly applied to any system that performs measurement using an image captured by a camera.

Explanation of Reference Numerals

[0040] 1... Measuring device, 2... Stereo camera, 3... Abnormality prompting device, 11... Rear - end - target region setting unit, 12... Rear - end processing unit, 13... Separation distance measurement unit, 14... Defective region calculation unit, 15... Motion vector calculation unit, 16... Actual - distance conversion coefficient calculation unit, 17... Motion state calculation unit, 21... First camera, 22... Second camera.

Claims

1. A measurement system for performing measurement, measurement means for performing the measurement using a captured image that is an image of an object captured by a camera; The image space is divided into a plurality of evaluation unit blocks each consisting of one or more pixels. For each evaluation unit block, a plurality of captured images selected from among the captured images during a period of a predetermined time length are used as evaluation target images, and the absolute value of the difference in the image attribute value of the evaluation unit block between temporally adjacent evaluation target images is obtained. An evaluation value calculation means for calculating the sum of the obtained absolute values of the differences as the evaluation value of the evaluation unit block; Defective area identification means for identifying, as a defective area, a set of defective blocks that are evaluation unit blocks for which the evaluation value obtained by the evaluation value calculation means is not included in a predetermined pass range, and which is an area unsuitable for use by the measurement means for measurement; The image attribute value of the evaluation unit block is a value determined by the pixel values of the respective pixels within the evaluation unit block, The measurement system, a target area setting means for setting a target area in the captured image; search means for searching, as a tracking result area, an area in the current captured image that matches the target area set by the target area setting means in the previous time; In each measurement, a movement amount calculation means for calculating a movement amount on the captured image from the target area set by the target area setting means in the previous time to the tracking result area searched by the search means in the current time, and converting the calculated movement amount on the captured image into a relative movement amount of the camera with respect to the object; The measurement system, wherein the target area setting means sets the target area so as not to include the defective area set by the defective area identification means.

2. The measurement system according to claim 1, wherein the pixel value of the pixel is the luminance value of the pixel, The measurement unit block is a region consisting of one pixel, and the image attribute value of the measurement unit block is the luminance value of one pixel included in the measurement unit block of the image to be measured, characterized by the measurement system.

3. The measurement system according to claim 1, The pixel value of the pixel is the luminance value of the pixel, The measurement unit block is a region consisting of a plurality of pixels, and the image attribute value of the measurement unit block is any one of the average value of the luminance values of a plurality of pixels included in the measurement unit block of the image to be measured, the histogram of the luminance values, and the spectrum of the spatial frequency of the luminance values, characterized by the measurement system.

4. The measurement system according to claim 1, 2 or 3, The qualified range does not include the sum greater than or equal to the first predetermined value, and does not include the sum less than the second predetermined value which is smaller than the first predetermined value, characterized by the measurement system.

5. The measurement system according to claim 1, 2, 3 or 4, The evaluation value calculation means calculates the evaluation value of the measurement unit blocks within the group by using a plurality of different captured images as the image to be measured for each group of one or more measurement unit blocks, characterized by the measurement system.

6. The measurement system according to claim 1, 2, 3, 4 or 5, When the size of the defective region identified by the defective region identification means becomes equal to or greater than a predetermined level, it has an abnormality presentation means for presenting the occurrence of an abnormality, characterized by the measurement system.

7. The measurement system according to claim 1, 2, 3, 4, 5 or 6, The search means excludes the defective region identified by the defective region identification means from the search target and performs the search for the tracking result region, characterized by the measurement system.

8. The measurement system according to claim 1, 2, 3, 4, 5, 6 or 7, The rear - tracked area setting means estimates, from the history of the amount of movement on the captured image calculated above, the amount of movement of the image in the next captured image relative to the image in the current captured image as a predicted amount of movement, and sets the rear - tracked area so that the area moved by the predicted amount of movement does not include the defective area set by the defective area identifying means. A measurement system characterized by this.

9. The measurement system according to claim 1, 2, 3, 4, 5, 6, 7 or 8, wherein The camera is mounted on a moving body, and the measurement system for the amount of movement is characterized in that the running surface on which the moving body runs is photographed as the object.

10. A measurement system for performing measurement, measurement means for performing the measurement using a captured image that is an image of an object captured by a camera; The image space is divided into a plurality of evaluation unit blocks each consisting of one or more pixels. For each evaluation unit block, a plurality of captured images selected from among the captured images during a period of a predetermined time length are used as evaluation target images, and the absolute value of the difference in the image attribute values of the evaluation unit block between temporally adjacent evaluation target images is obtained. An evaluation value calculating means for calculating the sum of the obtained absolute values of the differences as the evaluation value of the evaluation unit block; defective area identifying means for identifying, as a defective block, an evaluation unit block in which the evaluation value obtained by the evaluation value calculating means is not included in a predetermined pass range, and identifying the set of defective blocks as a defective area that is an area unsuitable for the measurement means to use for measurement; The image attribute value of the evaluation unit block is a value determined by the pixel values of the respective pixels within the evaluation unit block, The pass range is characterized in that it does not include the sum greater than a first predetermined value and does not include the sum less than a second predetermined value that is smaller than the first predetermined value.

Images