JP6928785B2 - Imaging device, axle load measurement system, and imaging method - Google Patents

Description

The present disclosure relates to an imaging device and an imaging method for generating an captured image for measuring road surface displacement. Furthermore, the present disclosure relates to an axle load measuring system that measures the axle load of a vehicle using captured images.

For example, Patent Document 1 discloses a axle load meter correction method. According to this axle load meter correction method, an axle load sensor for measuring axle load is embedded in a vehicle's runway, a vehicle with a known axle load is allowed to pass on the runway, and the license plate of the vehicle is photographed with a camera. do. A vehicle can be identified from the imaged license plate, and the axle load value of the vehicle obtained at the same time can be used to correct the axle load meter.

Japanese Unexamined Patent Publication No. 2011-64462

The present disclosure provides an imaging device capable of clearly imaging a traveling path through which a vehicle passes.

The image pickup apparatus according to one aspect of the present disclosure includes an image pickup unit, a detection unit, a calculation unit, and a control unit. The imaging unit takes an image of the traveling path through which the vehicle passes, and generates an captured image in which the traveling path is captured. The detection unit detects the contact position where the vehicle comes into contact with the traveling path in the captured image. The calculation unit calculates the first luminance range based on the luminance distribution in the first luminance distribution of the traveling path including the contact position. The control unit determines the imaging conditions of the imaging unit based on the first luminance range, and controls the imaging unit using the determined imaging conditions.

An imaging method according to another aspect of the present disclosure includes a detection step, a calculation step, and a control step. The detection step is a step of detecting the contact position where the vehicle comes into contact with the traveling path in the captured image obtained by capturing the traveling path through which the vehicle passes. The calculation step is a step of calculating the first luminance range based on the luminance distribution in the first luminance distribution of the traveling path including the contact position. The control step is a step of determining the imaging conditions of the imaging unit based on the first luminance range and controlling the imaging unit using the determined imaging conditions.

According to the image pickup device and the image pickup method according to the present disclosure, it is possible to clearly image the traveling path through which the vehicle passes.

FIG. 1 is a diagram schematically showing an example of measuring the axle load according to the embodiment. FIG. 2 is a block diagram showing a configuration of an imaging device according to an embodiment. FIG. 3 is a block diagram showing the configuration of the axle load measuring device according to the embodiment. FIG. 4 is a data configuration diagram of the coefficient of variation. FIG. 5 is a flowchart illustrating the operation of the image pickup apparatus. FIG. 6 is a diagram showing an example of a captured image. FIG. 7 is a diagram showing another example of the captured image. FIG. 8A is a diagram showing an example of the luminance distribution. FIG. 8B is a diagram showing another example of the luminance distribution. FIG. 9 is a flowchart illustrating the operation of the axle load measuring device. FIG. 10 is a diagram showing still another example of the captured image.

The image pickup apparatus according to one aspect of the embodiment includes an image pickup unit, a detection unit, a calculation unit, and a control unit. The imaging unit takes an image of the traveling path through which the vehicle passes, and generates an captured image in which the traveling path is captured. The detection unit detects the contact position where the vehicle comes into contact with the traveling path in the captured image. The calculation unit calculates the first luminance range based on the luminance distribution in the first luminance distribution of the traveling path including the contact position. The control unit determines the imaging conditions of the imaging unit based on the first luminance range, and controls the imaging unit using the determined imaging conditions.

As a result, this imaging device can clearly image the traveling path through which the vehicle passes. Therefore, the accuracy of the axle load measuring device using the image can be maintained.

It should be noted that these comprehensive or specific embodiments may be realized in a recording medium such as a system, method, integrated circuit, computer program or computer-readable CD-ROM, and the system, method, integrated circuit, computer program. Alternatively, it may be realized by any combination of recording media.

Hereinafter, a specific example of the image pickup apparatus according to one aspect of the present disclosure will be described. It should be noted that all of the embodiments described below show a preferred specific example of the present disclosure. Numerical values, shapes, materials, components, arrangement positions and connection forms of components, steps, order of steps, etc. shown in the following embodiments are examples, and are not intended to limit the present disclosure. The present disclosure is limited only by the scope of claims. Therefore, among the components in the following embodiments, the components not described in the independent claims indicating the highest level concept of the present disclosure are not necessarily necessary for achieving the subject of the present disclosure, but more. Described as constituting a preferred form.

(Embodiment 1)
Here, as one aspect of the present disclosure, the operation in the axle load measuring system installed on the traveling path of a general vehicle will be described.

Hereinafter, the image pickup apparatus will be described with reference to the drawings on the assumption that the image pickup device is incorporated in the axle load measurement system and operates.

[1-1. composition]
FIG. 1 is a diagram schematically showing an example of how the axle load measuring system 1 according to the embodiment measures the axle load of the vehicle 102. The axle load measuring system 1 includes an imaging device 100 and an axle load measuring device 200.

Here, for example, the axle load measuring device 200 is connected to the imaging device 100. The image pickup apparatus 100 takes an image of the traveling path 103 on which the vehicle 102 travels, and generates an captured image in which the traveling path 103 is captured. Then, a plurality of captured images generated by the imaging device 100 are input to the axle load measuring device 200. The axle load measuring device 200 measures the axle load of the vehicle 102 using the input captured image. Here, the vehicle 102 is, for example, a truck, and the traveling path 103 is, for example, an asphalt road.

FIG. 2 is a block diagram showing the configuration of the image pickup apparatus 100 according to the first embodiment of the present disclosure. The image pickup apparatus 100 includes an image pickup unit 110, a tire detection unit 120, an analysis unit 130, and a control unit 140. Further, the analysis unit 130 includes an area setting unit 131. The tire detection unit 120 is an example of the detection unit. The analysis unit 130 is an example of a calculation unit.

The imaging unit 110 images the travel path 103 based on externally controllable imaging conditions (including at least one item such as exposure time, aperture, gain, and black level), and the imaging image captured by the travel path 103. To generate. The image pickup unit 110 outputs the captured image captured by the traveling path 103 to the tire detection unit 120 and the axle load measuring device 200. The output of the captured image to the axle load measuring device 200 is performed by wireless or wired communication, or via a recording medium.

The tire detection unit 120 performs image recognition processing on the captured image generated by the image capturing unit 110. Then, the tire detection unit 120 recognizes the tire of the traveling vehicle in the captured image, and detects the position (contact position) where the tire touches the traveling path.

The area setting unit 131 sets a first road surface region including a position where the tire detected by the tire detection unit 120 touches the traveling road on the captured image. The first road surface area is an area affected by the axle load of the vehicle.

The analysis unit 130 generates a luminance distribution of the image in the first road surface region set by the region setting unit 131, and analyzes the luminance distribution. The analysis unit 130 calculates the first luminance range based on the luminance distribution. The first luminance range will be described later.

The control unit 140 determines the imaging conditions of the imaging unit 110 based on the first luminance range calculated by the analysis unit 130, and controls the imaging unit 110 using the determined imaging conditions. The control unit 140 sets the determined imaging conditions in the imaging unit 110. The imaging unit 110 may hold a predetermined imaging condition. The control unit 140 controls the image pickup unit 110 using predetermined imaging conditions, for example, in the initial state of the image pickup apparatus 100. The predetermined imaging condition is also used when the analysis unit 130 cannot calculate the first luminance range.

FIG. 3 is a block diagram showing the configuration of the axle load measuring device 200 according to the first embodiment of the present disclosure. As shown in FIG. 3, the axle load measuring device 200 includes an input unit 210, a detection unit 220, an axle load calculation unit 230, and a storage unit 240. Further, the detection unit 220 includes an axle load position specifying unit 221 and a displacement amount detecting unit 222.

The input unit 210 receives inputs of a plurality of captured images generated by the imaging device 100. Here, the input unit 210 accepts, for example, the input of a digital image of 4096 × 2160 pixels. The input of the captured image is performed by wireless or wired communication, or via a recording medium.

The detection unit 220 detects the amount of displacement corresponding to the displacement generated on the road surface of the traveling path by the passage of the vehicle at a predetermined point.

When the captured image received by the input unit 210 includes a vehicle, the axle load position specifying unit 221 specifies the axle load position of the vehicle in the captured image. More specifically, the axle load position specifying unit 221 performs image recognition processing on the captured image and determines whether or not the captured image includes a vehicle. Then, when it is determined that the vehicle is included, the axle load position specifying unit 221 recognizes the tire of the vehicle by further image recognition processing, and axes the region on the traveling road corresponding to the lowest point of the tire. Specify as a heavy position.

The displacement amount detection unit 222 detects the displacement amount in the captured image corresponding to the displacement generated in the traveling path due to the addition of the axle load by using the captured image obtained by capturing the traveling path of the vehicle. In particular, when the axle load position is specified by the axle load position specifying unit 221, the displacement amount detecting unit 222 detects the displacement amount corresponding to the displacement at the specified axle load position. That is, the displacement amount detection unit 222 compares the captured image in which the traveling path is not displaced and the captured image in which the traveling path is displaced among the plurality of captured images received by the input unit 210. Then, the amount of displacement is detected. The detection of the amount of displacement between captured images can be realized by using block matching, a correlation method, or an optical flow. This displacement amount is calculated as, for example, the number of pixels indicating the difference in the pixel positions corresponding to the same points on the traveling path between the captured images to be compared. Further, the captured image in which the displacement does not occur may be an captured image in which the traveling path is imaged in a state where the axial weight object does not exist in advance, or a plurality of imaging images in which the traveling path is continuously imaged in time. In the image, it may be a captured image in which the amount of change in the image is a certain amount or less, or it may be a captured image in which it is determined by the image recognition process that there is no axially weighted object.

The storage unit 240 stores the first information indicating the relationship between the axle load and the displacement amount. More specifically, the storage unit 240 has a relational expression showing the relationship between the axle load and the amount of displacement when the displacement occurs in the traveling path due to the addition of the axle load to the traveling path, and the relational expression thereof. The displacement coefficient, which is a coefficient used in the relational expression, is stored as the first information. The storage unit 240 may be realized by a memory (not shown) constituting the axle load measuring device 200, or may be realized by a database of a communicable external device.

Generally, the axle load w (kg) is expressed by the formula w = f (d) as a function f of the displacement amount d (the number of pixels). Here, the function f is approximated by a linear expression and treated. Therefore, the storage unit 240 stores a linear expression (w = αd) represented by a variable as d and a coefficient as α as a relational expression, and stores the coefficient α as a displacement coefficient.

The displacement coefficient α has a displacement coefficient value associated with each position that can be specified as the axle load position by the axle load position specifying unit 221. This reflects that the distance from the imaging position is different from each other, the composition of asphalt and the like is different from each other, the road surface temperature is different from each other, the deterioration state of the road surface is different from each other, etc. for each region on the traveling road. Can be done. Here, the coefficient of variation α is set locally for each region (hereinafter, referred to as “local region”) of the captured image, for example, 10 pixels in the horizontal direction (x direction) and 10 pixels in the vertical direction (y direction). It has a value corresponding to the region.

FIG. 4 is a diagram showing an example of the displacement coefficient α stored by the storage unit 240. The axle load calculation unit 230 calculates the axle load of the vehicle existing on the traveling road based on the displacement amount detected by the detection unit 220 and the first information stored by the storage unit 240. In particular, when the axle load position is specified by the axle load position specifying unit 221, the axle load calculation unit 230 calculates the axle load based on the displacement amount at the specified axle load position. More specifically, the axle load calculation unit 230 sets the displacement amount d detected by the displacement amount detection unit 222 as a displacement coefficient value corresponding to a region including the axle load position specified by the axle load position identification unit 221. By multiplying, the axle load w is calculated.

In the axle load measuring system 1 having the above configuration, the measurement accuracy of the axle load measuring device 200 depends on the sharpness of the captured image captured by the imaging device 100. The image pickup device 100 of the present disclosure generates an image captured image suitable for the axle load measuring device 200 to measure the axle load. In other words, the image pickup device 100 generates an image pickup image in which the image near the tire is clear, which is particularly used for the detection unit 220 of the axle load measuring device 200.

Hereinafter, the operation performed by the imaging apparatus 100 of the present disclosure will be described with reference to the drawings.

[1-2. motion]
[1-2-1. Imaging]
FIG. 5 is a flowchart illustrating the operation of the image pickup apparatus. FIG. 6 is a diagram showing an example of a captured image. FIG. 7 is a diagram showing another example of the captured image.

FIG. 6 shows a captured image including a vehicle (hereinafter, referred to as “captured image A”). The captured image A includes a vehicle 102 traveling on the traveling path 103. Then, the vehicle 102 is in contact with the traveling path 103 at the lowest point 610 of the tire 600.

Further, FIG. 7 shows a captured image (hereinafter, referred to as “captured image B”) that does not include the vehicle. The captured image A and the captured image B are images in which the traveling path 103 is captured from the same viewpoint. The region 710 on the travel path 103 in the captured image B is the same region as the region on the travel path 103 corresponding to the lowest point 610 of the tire in the captured image A. Further, the region 720 on the travel path 103 in the captured image B is the same region as the region 640 on the travel path 103 in the captured image A.

First, the imaging unit 110 images the traveling path 103 based on predetermined imaging conditions (including at least one item such as exposure time, aperture, gain, black level, etc.) under the control of the control unit 140 (including at least one item such as exposure time, aperture, gain, and black level). Step S51).

The tire detection unit 120 performs image recognition processing on the captured image generated by the imaging unit 110, and recognizes the tire 600 of the traveling vehicle 102 in the captured image (step S52).

If the tire detection unit 120 does not recognize the tire, the process returns to step S51. When the tire detection unit 120 recognizes the tire, the process proceeds to step S53. For example, when the image generated by the imaging unit 110 is the captured image A in FIG. 6, the tire detecting unit 120 recognizes the tire 600 and sets the contact position between the tire 600 and the traveling path 103 as the lowest point directly below the tire 600. Get 610. Further, when the captured image generated by the imaging unit 110 is the captured image B in FIG. 7, the tire is not detected, so the process returns to step S51.

The area setting unit 131 sets the first road surface area 630 including the lowest point 610 on the captured image A based on the position of the tire 600 detected by the tire detection unit 120 (step S53). The first road surface region 630 is a region affected by the axle load of the vehicle 102 via the tire 600 (step S54). In the case of the captured image A, the area setting unit 131 sets the road surface on the front side of the vehicle 102, the road surface on the rear side of the vehicle 102, or the road surface on the front side of the vehicle 102 with reference to the lowest point 610. It is set as the road surface area 630 of 1. The size of the first road surface area 630 may be set in advance. Further, the size of the first road surface region 630 may be set based on the detected size of the tire 600. Further, the size of the first road surface region 630 may be set based on the displacement detection result of the road surface described later.

The analysis unit 130 generates a luminance distribution from the captured image in the first road surface region 630 set by the region setting unit 131, and analyzes the luminance distribution. Specifically, the analysis unit 130 generates a luminance histogram of the first road surface region 630. Then, the analysis unit 130 determines the upper limit value and the lower limit value of the brightness of the first road surface region 630, and outputs the range including the upper limit value and the lower limit value as the first brightness range.

FIG. 8A is a diagram showing an example of the luminance distribution. FIG. 8B is a diagram showing another example of the luminance distribution. In FIGS. 8A and 8B, the horizontal axis represents the luminance and the vertical axis represents the frequency of the luminance.

FIG. 8A is an example of the luminance histogram of the entire captured image A of FIG. The brightness histogram of FIG. 8A shows that in the captured image A, pixels having low brightness to pixels having high brightness are present. On the other hand, FIG. 8B is an example of the luminance histogram of the first road surface region 630. That is, FIG. 8B shows the luminance distribution of the pixels in which the traveling path 103 is imaged. In general, pixels in which an asphalt pavement runway is imaged tend to have low brightness. In addition, when the vehicle passes by, the sunshine and the illumination light are blocked, so that the traveling path near the tires may become darker. Compared with the luminance histogram of FIG. 8A, it can be seen that the frequency of low-luminance pixels is higher in the luminance histogram of FIG. 8B.

The analysis unit 130 determines the upper limit value 802 and the lower limit value 801 of the brightness to be imaged based on the brightness distribution of FIG. 8B. The upper limit does not necessarily have to be the upper end of the luminance distribution. Further, the lower limit value does not necessarily have to be the lower end of the luminance distribution. The upper limit value may be set to a value of the upper 5% of the luminance distribution, or may be set to a value in which a certain margin is added to the upper end. Similarly, the lower limit value may be set to a value of the lower 5% of the luminance distribution, or may be set to a value in which a certain margin is added to the lower end.

In the above example, the control unit 140 determines the upper limit value 802 and the lower limit value 801 based only on the first road surface region 630 including the road surface covered by the axle load. However, the control unit 140 sets a road surface region (second road surface region 620) other than the first road surface region 630, and is based on the brightness range (second brightness range) and the first brightness range in the road surface region. , The imaging conditions of the imaging unit 110 may be determined (see FIG. 6). The second road surface region 620 is a comparative road surface region that the axle load does not reach, and is a region separated from the first road surface region 630 by a predetermined distance or more. When the second road surface region 620 is used, the control unit 140 generates a brightness distribution (luminance histogram) in the second road surface region 620, analyzes the brightness distribution, and calculates the second brightness range. Then, the control unit 140 may determine the upper limit value and the lower limit value of the brightness to be imaged based on the first brightness range and the second brightness range. As a result, it is expected that the accuracy of the action of suppressing the influence of the shaking of the image pickup apparatus 100 in the axial load measurement using the image described later will be improved.

Further, the analysis unit 130 determines whether or not the calculated first luminance range satisfies a predetermined condition, and if the first luminance range does not satisfy the predetermined condition, saves the analyzed captured image. You may. Alternatively, the analysis unit 130 may notify that the analyzed captured image is abnormal when the first luminance range does not satisfy a predetermined condition. As a result, the user of the image pickup apparatus 100 can know that the captured image is abnormal. The case where the predetermined condition is not satisfied is, for example, a case where the pixel values of the target image area are concentrated on almost the same value and the upper limit value 802 and the lower limit value 801 are substantially equal (the brightness range is calculated). If you can't) etc.

The control unit 140 determines the imaging conditions based on the brightness range calculated by the analysis unit 130. The control unit 140 adjusts the imaging conditions including at least one item such as the aperture, gain, exposure time, and black level of the imaging unit 110 so that the calculated luminance range corresponds to the luminance range that can be imaged. The control unit 140 can determine the imaging conditions in the same manner as a normal camera imaging. Here, the control unit 140 can set an upper limit on the exposure time in order to avoid image blurring and maintain the frame rate. Further, when the amount of light received is sufficient, the control unit 140 can maintain the accuracy of displacement detection using an image described later by giving priority to lowering the gain (step S55).

Once the imaging conditions are set improperly, the tires will continue to be undetected. In order to avoid such a state, the control unit 140 may control the image pickup unit 110 under predetermined imaging conditions when the tire is not detected for a predetermined period.

Finally, the control unit 140 sets the imaging conditions in the imaging unit 110. That is, the control unit 140 controls the image pickup unit 110 using the determined imaging conditions (step S56). The control unit 140 updates the imaging conditions in units of the shortest frame rate. However, if the time required from steps S51 to S56 becomes long, the control unit 140 may update the imaging conditions with a delay of several frames. That is, the target tire may be included in the captured image. Further, if the imaging conditions are updated in units of a small number of frames by sequential control, proper shooting may not be possible due to a time delay in control. In order to avoid this, the control unit 140 may control the image pickup unit 110 according to the passage of the vehicle that has detected the tire. That is, the control unit 140 may control the imaging unit 110 using the determined imaging conditions for a predetermined period (the period from the time when the imaging conditions for the ground contact position are changed next) after the imaging conditions are determined. .. As a result, the imaging unit 110 can satisfactorily image the vehicle from the first frame in which the next vehicle enters the imaging range.

[1-2-2. Measurement processing]
The measurement process is a process of calculating the axle load of a vehicle when an captured image including the vehicle is input to the axle load measuring device 200. FIG. 9 is a flowchart illustrating the operation of the measurement process of the axle load measuring device.

This measurement process is started when the captured image A including the vehicle 102 is input to the input unit 210. When the measurement process is started, the input unit 210 acquires the captured image A input from the imaging device 101 (step S91).

When the captured image A is input, the axle load position specifying unit 221 performs image recognition processing to identify the lowest point 610 of the tire 600 of the vehicle 102. Then, the axle load position specifying unit 221 specifies the region on the traveling path 103 corresponding to the specified lowest point 610 as the axle load position (step S92).

Here, the axle load position specifying unit 221 does not necessarily have to specify one point (1 pixel) as the axle load position, and may specify a local image region composed of a plurality of adjacent pixels as the axle load position. The axle load position specifying unit 221 may limit the axle load detection range to be detected by the axle load to the region of the travel path 103, or may limit the axle load to a part of the travel path 103. The limited area may be designated by the user, or may be designated by the collaboration between the designation by the user and the image recognition of the color or texture of the travel path 103. By limiting the axle load detection range, there is an effect of suppressing the amount of image processing. Therefore, the amount of image processing for detecting the axle load position can be suppressed. When a plurality of tires are in contact with the traveling path 103 in the captured image, a plurality of axle load positions corresponding to the contact positions are detected.

When the axle load position is specified, the displacement amount detection unit 222 detects the displacement amount corresponding to the displacement generated in the traveling path at the specified axle load position (step S93). The displacement amount detection unit 222 detects the displacement amount by using the captured image A and the captured image B. If the captured image B has not been acquired by the input unit 210 by the time the axle load position is specified, the displacement amount detection unit 222 waits until the captured image B is acquired by the input unit 210, and then this displacement. Detect the amount.

The displacement amount detection unit 222 detects the displacement amount generated between the region on the traveling path 103 corresponding to the lowest point 610 in the captured image A and the region 710 in the captured image B. Here, the amount of displacement of the traveling path due to the axle load of a general vehicle is very small. Therefore, it is desirable to suppress the influence of the shaking of the image pickup apparatus 100 due to the vibration of the vehicle traveling on the traveling road. As an example, the displacement amount detection unit 222 determines the same points (for example, the region 640 in the captured image A and the region 720 in the captured image B) that are not specified to be the axial load positions in both the captured image A and the captured image B. elect. Then, the displacement amount detection unit 222 calculates the displacement amount between the selected regions (hereinafter, referred to as “non-axial load position displacement amount”). Then, the displacement amount detection unit 222 determines the non-axial load position from the displacement amount generated between the region on the traveling path 103 corresponding to the lowest point 610 of the tire in the captured image A and the region 710 in the captured image B. The displacement amount is subtracted to correct the displacement amount. This makes it possible to suppress the influence of the shaking of the image pickup apparatus 100. In addition, the influence of the shaking of the image pickup apparatus 100 can be suppressed by a method using an optical image stabilization technique, a method using a mechanical mechanism such as a sensor shift method, or the like.

When the displacement amount is detected, the axle load calculation unit 230 specifies the displacement coefficient value corresponding to the axle load position specified by the axle load position specifying unit 221 (step S94). That is, the axle load calculation unit 230 specifies the displacement coefficient value corresponding to the axle load position specified by the axle load position identification unit 221 with reference to the displacement coefficient α (see FIG. 4) stored in the storage unit 240. do.

When the displacement coefficient value is specified, the axle load calculation unit 230 calculates the axle load by multiplying the specified displacement coefficient value by the displacement amount detected by the displacement amount detection unit 222 (step S95). ..

When the axle load is calculated, the axle load calculation unit 230 outputs the calculated numerical value of the axle load to the outside (step S96). Here, instead of outputting the calculated axle load value to the outside, the axle load calculation unit 230 informs the user when the calculated axle load value is larger than a predetermined reference value. It may be notified.

When the process of step S96 is completed, the axle load measuring device 200 ends the measurement process. The axle load measuring device 200 has an input unit 210 for inputting an image, and detects the position of the tire by image recognition.

[1-3. Effect, etc.]
As described above, the image pickup apparatus 100 appropriately images the road surface region covered by the axle load of the vehicle 102. Under general imaging conditions, the brightness of the pixels captured on the asphalt road surface, especially the road surface where the shadow of the vehicle body is cast, becomes low, and a clear image cannot be obtained.

In the first embodiment, the tire detection unit 120 detects the position where the tire 600 of the vehicle 102 comes into contact with the travel path 103. The area setting unit 131 sets the first road surface area including the position where the axle load is applied. The analysis unit 130 analyzes the brightness distribution of the road surface region and calculates the first brightness range. The control unit 140 sets the imaging conditions of the imaging unit 110 based on the first luminance range. As a result, a clear captured image capable of detecting the road surface displacement with high accuracy can be obtained.

Further, the analysis unit 130 analyzes the brightness distribution in the second road surface region that is not affected by the axle load, and calculates the second brightness range. The control unit 140 sets the imaging conditions based on the first luminance range and the second luminance range. As a result, it is possible to appropriately obtain an image necessary for correcting the influence of the blur of the image pickup unit 110 (suppressing the influence of the camera shake).

[1-4. Modification example]
The axle load measuring device according to the modified example will be described with reference to FIGS. 3 and 10.

In the above description, the axle load measuring device 200 corrects the displacement amount due to the axle load of the vehicle 102 by using the displacement amount of the region 640 (see FIG. 6) which is not specified as the axle load position. Here, when the imaging device 100 images the traveling path 103 under the imaging conditions suitable for the first road surface region 630 and generates the captured image, the brightness range in the region for correction such as the region 640 is displaced. It may deviate from the suitable brightness range. Then, the error of the displacement amount detection in the region for correction becomes large, and the error of the displacement amount calculation indicating the axle load of the vehicle 102 also becomes large. Therefore, the axle load measuring device according to this modification specifies the area for correction based on the brightness range in the area for detecting the displacement amount.

The axle load position specifying unit 221 identifies a region 650 (third road surface region) of the traveling path 103 including the lowest point 610 (contact position) and the lowest point 610 in the captured image shown in FIG. Then, the axle load position specifying unit 221 calculates the brightness range (third brightness range) based on the brightness distribution in the region 650. The axle load position specifying unit 221 identifies a region 660 (fourth road surface region) having a luminance range substantially the same as the luminance range in the region 650 or a luminance range narrower than the luminance range in the region 650 in the captured image. do. The region 660 is a region that does not include the region 650 and is not easily affected by the axle load of the vehicle 102. The region 660 may be a region separated from the region 650 by a predetermined distance or more.

The displacement amount detection unit 222 detects the displacement amount (contact position displacement amount) of the traveling path 103 at the lowest point 610. At this time, the displacement amount detection unit 222 may detect the displacement amount of the region 650 by comparing with the captured image that does not include the vehicle as shown in FIG. 7. Similarly, the displacement amount detection unit 222 detects the displacement amount (comparative displacement amount) of the traveling path 103 in the region 660.

The axle load calculation unit 230 calculates the axle load of the vehicle 102 based on the displacement amount of the lowest point 610 and the displacement amount of the region 660. Specifically, the axle load calculation unit 230 calculates the axle load of the vehicle 102 by subtracting the displacement amount of the region 660 from the displacement amount of the lowest point 610.

By the above operation, the axle load measuring device 200 according to the present modification has the same luminance range as the luminance range of the region 650 for calculating the axle load, or the region 660 having a luminance range narrower than the luminance range of the region 650. The axle load of the vehicle 102 is corrected by using the displacement amount of. The luminance range of the region 660 is set by the image pickup apparatus 100 to a luminance range suitable for detecting the displacement amount, similarly to the luminance range of the region 650. Therefore, the axle load measuring device 200 can accurately correct the axle load of the vehicle 102 by using the displacement amount of the region 660. That is, the axle load measuring device 200 can accurately measure the axle load of the vehicle 102.

(Other embodiments)
As described above, embodiments have been described as an example of the techniques disclosed in this application. However, the technique in the present disclosure is not limited to these, and can be applied to embodiments in which changes, replacements, additions, omissions, etc. are made as appropriate.

(1) In the first embodiment, the image pickup device 100 and the axle load measuring device 200 recognize the tire of the vehicle by image processing, and specify the region on the traveling road corresponding to the lowest point of the tire as the axle load position. It has been described as an example of the configuration. However, the method for specifying the axle load position is not necessarily limited to the above method. For example, the image pickup apparatus 100 and the axle load measuring apparatus 200 may specify the position where the displacement amount is locally maximized as the axle load position.

(2) In the first embodiment, the captured image may be a monochrome image, a color image, or a multispectral image. In addition to visible light, the light to be imaged may be ultraviolet light, near-infrared light, or far-infrared light.

(3) In the first embodiment, an example of asphalt pavement has been used as the road surface of the traveling path 103. However, the road surface of the traveling road 103 may be a road surface made of other pavement materials such as concrete in addition to asphalt pavement. Further, the road surface of the traveling road 103 may be a road surface in which the pavement surface is partially covered with a plate material, a sheet material, a paint or the like. Further, in order to obtain the displacement by the image more accurately and remarkably, the road surface of the traveling path 103 may be covered with the above-mentioned material, and the covered area may be used as the target area for displacement detection.

(4) In the embodiment, each component (functional block) in the image pickup apparatus 100 may be individually integrated into one chip by a semiconductor device such as an IC (Integrated Circuit) or an LSI (Large Scale Integration). It may be made into one chip so as to include a part or the whole. Further, the method of making an integrated circuit is not limited to LSI, and may be realized by a dedicated circuit or a general-purpose processor. An FPGA (Field Programmable Gate Array) that can be programmed after the LSI is manufactured, or a reconfigurable processor that can reconfigure the connection and settings of circuit cells inside the LSI may be used. Furthermore, if an integrated circuit technology that replaces an LSI appears due to advances in semiconductor technology or another technology derived from it, functional blocks may be integrated using that technology. The application of biotechnology, etc. is possible.

Further, all or part of the above-mentioned various processes may be realized by hardware such as an electronic circuit or may be realized by software. The processing by the software is realized by the processor included in the image pickup apparatus executing the program stored in the memory. Further, the program may be recorded on a recording medium and distributed or distributed. For example, by installing the distributed program on a device having another processor and causing the processor to execute the program, it is possible to cause the device to perform each of the above processes.

Further, the scope of the present disclosure also includes a form realized by arbitrarily combining the components and functions shown in the above-described embodiment.

The present disclosure can be used in an imaging device that generates an captured image for measuring road surface displacement.

1 Axial load measurement system 100 Imaging device 110 Imaging unit 120 Tire detection unit (detection unit)
130 Analysis Department (Calculation Department)
131 Area setting unit 140 Control unit 200 Axis load measuring device 210 Input unit 220 Detection unit 221 Axis load position identification unit 222 Displacement amount detection unit 230 Axis load calculation unit 240 Storage unit

Claims (13)

An imaging unit that captures an image of a traveling path through which a vehicle passes and generates an captured image of the traveling path.
In the captured image, a detection unit that detects a contact position where the vehicle comes into contact with the traveling path, and a detection unit.
A calculation unit that calculates the first luminance range based on the luminance distribution in the first luminance distribution of the traveling path including the contact position.
A control unit that determines the imaging conditions of the imaging unit based on the first luminance range and controls the imaging unit using the determined imaging conditions.
Imaging device equipped with. The imaging device according to claim 1, wherein the detection unit detects the contact position by recognizing the tire of the vehicle. The calculation unit calculates a second luminance range based on the luminance distribution in the second luminance distribution of the traveling road that is separated from the first luminance region by a predetermined distance or more.
The imaging device according to claim 1 or 2, wherein the control unit determines the imaging conditions based on the first luminance range and the second luminance range. The imaging device according to claim 3, wherein the predetermined distance is a distance to a region where the axle load of the vehicle does not reach. The imaging device according to any one of claims 1 to 4, wherein the imaging condition includes at least one item of the aperture, gain, exposure time, or black level of the imaging unit. The imaging device according to claim 1, wherein the control unit controls the imaging unit using the imaging conditions for a predetermined period after determining the imaging conditions. The imaging device according to claim 2, wherein the control unit controls the imaging unit using predetermined imaging conditions when the detecting unit does not recognize the tire of the vehicle for a predetermined period of time. The calculation unit determines whether or not the first luminance range satisfies a predetermined condition, and if it is determined that the first luminance range does not satisfy the predetermined condition, the captured image is saved. , The imaging apparatus according to claim 1. The calculation unit determines whether or not the first luminance range satisfies a predetermined condition, and if it determines that the first luminance range does not satisfy the predetermined condition, the captured image is abnormal. The imaging device according to claim 1, which notifies that there is. The imaging device according to claim 1 and
An axle load measuring device that measures the axle load of the vehicle using the captured image, and
Axial load measurement system equipped with. The axle load measuring device is
In the captured image, the axle load position specifying portion for specifying the contact position and the axle load position specifying portion
A displacement amount detection unit that detects the contact position displacement amount, which is the displacement amount at the contact position,
The axle load measuring system according to claim 10, further comprising an axle load calculating unit that calculates the axle load based on the contact position displacement amount. The axle load position specifying portion is
A third road surface region of the traveling path including the contact position is specified.
A third luminance range is calculated based on the luminance distribution in the third road surface region.
In the captured image, a fourth road surface region having the same brightness range as the third brightness range or a brightness range narrower than the third brightness range and not including the third road surface region is specified. ,
The displacement amount detection unit is
A comparative displacement amount, which is a displacement amount in the fourth road surface region, is detected.
The axle load calculation unit
The axle load measuring system according to claim 11, wherein the axle load is calculated based on the contact position displacement amount and the comparative displacement amount. In the captured image of the traveling path through which the vehicle passes, a detection step of detecting a contact position where the vehicle contacts the traveling path, and a detection step.
A calculation step of calculating the first luminance range based on the luminance distribution in the first luminance distribution of the traveling path including the contact position, and
A control step of determining the imaging conditions of the imaging unit based on the first luminance range and controlling the imaging unit using the determined imaging conditions.
Imaging method including.

Images