JP2022042409A - Method for comparing continuous temperature, method for assaying specific temperature region, information processor, continuous temperature comparison system, specific temperature region assay system, and program - Google Patents

Abstract

To allow a proper diagnosis of progress of damages in the diagnosis of the soundness of a paved road by using an infrared thermal image.SOLUTION: A computer specifies the same damaged part between a plurality of infrared thermal images with different diagnosis frequencies, on the basis of the correspondence between pixels in the infrared thermal images and the position on a paved road in a predetermined coordinate system set on the paved road and temperature information of the damaged part in the infrared thermal images for the damaged part of the paved road detected from the infrared thermal images of the pave road taken by an infrared thermo-camera.SELECTED DRAWING: Figure 9

Description

The present invention relates to a continuous temperature comparison method, a specific temperature region verification method, an information processing device, a continuous temperature region verification system, a specific temperature region verification system, and a program, and more particularly to a diagnosis of the soundness of a paved road using an infrared thermal image. ..

As one of the methods for diagnosing the soundness of paved roads such as highways, an infrared thermal image of the paved road is taken with an infrared thermo camera installed in a traveling vehicle, and the infrared thermal image is analyzed to damage the paved road. There is a way to diagnose the presence or absence of. For example, Patent Document 1 discloses a road surface defect detection system and a method for identifying a type of a defect on a detected road surface by analyzing an infrared thermal image of the detected road surface.

In this type of diagnostic method, the presence / absence, type, degree (damage level), etc. of damage are diagnosed by utilizing the temperature difference between a healthy part and a damaged part of a paved road.

Japanese Unexamined Patent Publication No. 2012-177675

One of the important things in diagnosing the soundness of paved roads is to properly diagnose the change over time of the damaged part, that is, the progress of the damage. By appropriately diagnosing the progress of the injury, it is possible to predict when the injury needs to be dealt with and take appropriate measures before the injury becomes severe.

However, it is difficult to properly diagnose the progress of damage by the conventional diagnostic method using infrared thermal images.

In one aspect, it is an object of the present invention to provide a technique capable of appropriately diagnosing the progress of damage in the diagnosis of the soundness of a paved road using an infrared thermal image.

In the continuous temperature comparison method according to one embodiment, the pixels in the infrared thermal image and the pavement of the damaged portion of the paved road detected by the computer from the infrared thermal image of the paved road taken by the infrared thermo camera. Same among multiple infrared thermal images with different diagnosis times based on the correspondence with the position on the paved road in a predetermined coordinate system set on the road and the temperature information of the damaged portion in the infrared thermal image. It is a continuous temperature comparison method to identify the damaged part of the road.

In the specific temperature region verification method according to one embodiment, a computer derives an estimated healthy temperature of a healthy part of the paved road estimated from an infrared thermal image of the paved road taken by an infrared thermo camera, and the infrared heat is obtained. Among the pixels in the first region including the damaged position in the image, the ratio of the pixel whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the damaged position in the infrared thermal image are shown. Percentage of pixels in the second region that is smaller than the first region and whose absolute value of the temperature difference from the estimated healthy temperature is greater than or equal to the second threshold and greater than or equal to the first threshold. This is a specific temperature region verification method that calculates and outputs the calculated ratio of the pixels.

The information processing apparatus according to one aspect is set on the pixels in the infrared thermal image and the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. Based on the correspondence with the position on the paved road in the predetermined coordinate system and the temperature information of the damaged portion in the infrared thermal image, the same damaged portion is formed between a plurality of infrared thermal images having different diagnosis times. It is an information processing device provided with a control unit for specifying.

The information processing apparatus according to one aspect derives an estimated healthy temperature of a healthy part of the paved road estimated from an infrared thermal image of the paved road taken by an infrared thermo camera, and determines the damaged position in the infrared thermal image. Among the pixels in the first region including the pixel, the ratio of the pixel whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the damaged position in the infrared thermal image are included, and the first Of the pixels in the second region smaller than the region of, the ratio of the pixels whose absolute value of the temperature difference from the estimated healthy temperature is greater than or equal to the second threshold value larger than the first threshold value is calculated. , An information processing device including a control unit that outputs the calculated ratio of the pixels.

The continuous temperature comparison system according to one embodiment is set on the pixels in the infrared thermal image and the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. In the storage unit that stores the correspondence with the position on the paved road in the predetermined coordinate system and the temperature information of the damaged portion in the infrared thermal image, and in the infrared thermal image stored in the storage unit. A control unit that identifies the same damaged portion among a plurality of infrared thermal images having different diagnosis times based on the correspondence between the pixel and the position on the paved road and the temperature information of the damaged portion in the infrared thermal image. It is a continuous temperature comparison system including.

The specific temperature region verification system according to one embodiment is a storage unit that stores an infrared thermal image of a paved road taken by an infrared thermo camera and an estimated healthy temperature of a healthy part of the paved road estimated from the infrared image. And, among the pixels in the first region including the damaged position in the infrared thermal image, the ratio of the pixels whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value, and the infrared thermal image. Of the pixels in the second region smaller than the first region, including the damage position in the above, the absolute value of the temperature difference from the estimated healthy temperature is greater than or equal to the second threshold value larger than the first threshold value. It is a specific temperature region verification system including a control unit that calculates the ratio of the pixels and outputs the calculated ratio of the pixels.

A program according to one aspect is to the computer on the pixels in the infrared thermal image and on the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by an infrared thermo camera. The same damaged part among a plurality of infrared thermal images having different diagnosis times based on the correspondence with the position on the paved road in the set predetermined coordinate system and the temperature information of the damaged part in the infrared thermal image. It is a program that executes the process to specify.

A program according to one embodiment derives an estimated healthy temperature of a healthy part of the paved road estimated from an infrared thermal image of the paved road taken by an infrared thermo camera, and includes a damaged position in the infrared thermal image. The first region includes the proportion of pixels in one region whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the damaged position in the infrared thermal image. Calculate and calculate the percentage of pixels in the second region that is smaller than the second threshold and whose absolute value of the temperature difference from the estimated healthy temperature is greater than the first threshold and greater than or equal to the second threshold. It is a program that executes a process of outputting the ratio of the said pixels.

According to the above aspect, it is possible to appropriately diagnose the progress of damage in the diagnosis of the soundness of the paved road using the infrared thermal image.

It is a figure explaining the configuration example of the infrared automatic thermal analysis diagnosis system which concerns on one Embodiment. It is a block diagram which shows an example of the functional structure of the information processing apparatus which concerns on one Embodiment. It is a flowchart explaining an example of individual diagnosis processing. It is a block diagram explaining an example of the information to be stored in a storage part. It is a block diagram explaining an example of individual diagnosis data. It is a figure explaining an example of the image information of individual diagnosis data. Analysis of individual diagnostic data It is a figure explaining an example of diagnostic information. It is a figure explaining an example of the test information of the individual diagnostic data. It is a flowchart explaining an example of the continuous temperature comparison processing which concerns on one Embodiment. It is a figure explaining the correspondence relationship between the image taking area of an infrared thermal image on an actual paved road, and the position in an infrared thermal image. It is a figure explaining the example of the damage detected from the infrared thermal image. It is a figure explaining an example of the relationship between the moving direction of a vehicle, and a reference direction. It is a figure explaining an example of the derivation method of the point cloud coordinates. It is a figure explaining the example of the photographing range of the infrared thermal image including the same position on the road. It is a figure explaining the example of the search method of the same damage between thermal infrared images with different diagnosis times. It is a flowchart explaining an example of the specific temperature region verification process which concerns on one Embodiment. It is a figure explaining an example of the 1st region and the 2nd region set in the specific temperature region verification process. It is a figure explaining the hardware configuration example of a computer.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the following description, detailed description of well-known image processing applicable to analysis and diagnosis of infrared thermal images will be omitted.

FIG. 1 is a diagram illustrating a configuration example of an infrared automatic thermal analysis diagnostic system according to an embodiment. FIG. 1 shows an example of an infrared automatic thermal analysis diagnostic system 1 that diagnoses the soundness of a paved road 9 on which a vehicle 5 can travel by using an infrared thermal image.

The infrared automatic thermal analysis diagnostic system 1 exemplified in FIG. 1 includes an infrared thermo camera 2, a GPS (Global Positioning System) receiver 3, and an information processing device 4. The infrared thermo camera 2, the GPS receiver 3, and the information processing device 4 are installed in the vehicle 5 used for diagnosis at the time of diagnosis. Further, the information processing device 4 may be brought into the room from the vehicle 5 and used for diagnosis.

The infrared thermo camera 2 is a camera that detects infrared rays radiated from a subject and captures an infrared thermal image. The infrared thermo camera 2 is installed above the vehicle 5 by a mounting bracket 6 so as to capture an infrared thermal image in a predetermined photographing area R in front of the vehicle 5 on the paved road (road surface) 9 to be diagnosed. Will be done. When the extension direction of the imaging center VC of the infrared thermo camera 2 has a significant inclination with respect to the normal direction of the paved road 9, the imaging region R is directed from the end RN closest to the vehicle 5 to the end RF farthest from the end RN. It is a region of a substantially trapezoid (more specifically, a substantially isosceles trapezoid) in which the dimensions in the width direction (not shown) increase monotonically. The angle of view φ of the infrared thermo camera 2, the distance LG from the vehicle 5 to the shooting area R on the paved road 9, the area of the shooting area R (in other words, the dimension in the width direction of the end RN closest to the vehicle 5, the road). Dimensions such as LR in the stretching direction) are arbitrary.

The GPS receiver 3 is a position detection device that receives radio waves emitted by GPS satellites and derives the position (latitude and longitude) of the GPS receiver 3 on the earth. The GPS receiver 3 may be built in, for example, the infrared thermo camera 2. Further, as the GPS receiver 3 of the infrared automatic thermal analysis diagnosis system 1, for example, the GPS receiver included in the car navigation system installed in the vehicle interior of the vehicle 5 may be used. The GPS receiver 3 acquires the position information of the vehicle 5 (infrared thermo camera 2) when the infrared thermal image is taken by the infrared thermo camera 2 of the vehicle 5 traveling on the paved road 9 to be diagnosed. This is an example of an acquisition device.

The information processing device 4 acquires and analyzes an infrared thermal image taken by the infrared thermo camera 2 and automatically performs a process of diagnosing the soundness of the paved road 9 to be diagnosed. The information processing apparatus 4 exemplified in the present embodiment uses a set of infrared thermal images taken for one diagnosis of a paved road 9 as a process for diagnosing the soundness of the paved road 9 and damages the paved road 9. It includes a process of diagnosing the presence / absence and the damage level (hereinafter referred to as "individual diagnosis process") and a process of diagnosing the progress status of damage detected by the individual diagnosis process (hereinafter referred to as "progress status diagnosis process"). Further, the information processing apparatus 4 exemplified in the present embodiment acquires the position information (latitude and longitude) derived by the GPS receiver 3 and sets the latitude and longitude of each position on the paved road 9 in the infrared thermal image pixel by pixel. The process of calculating is automatically performed. The infrared thermo camera 2 and the GPS receiver 3 are each connected to the information processing device 4 by wireless communication or a transmission cable such as a USB (Universal Serial Bus) cable. The information processing device 4 may be, for example, a portable device capable of accumulating infrared thermal images and position information and then taking it out of the vehicle 5 to perform the above-mentioned analysis, diagnosis, and the like.

When diagnosing the soundness of the paved road 9 by the infrared automatic heat analysis diagnosis system 1 installed in the vehicle 5, the infrared heat taken by the infrared thermo camera 2 while the vehicle 5 is running on the paved road 9 to be diagnosed. The image and the position information of the vehicle 5 at the time of shooting are periodically transferred to the information processing apparatus 4. At this time, the vehicle 5 is such that the entire paved road 9 is diagnosed by connecting the partial regions of the paved road 9 to be diagnosed in each of the plurality of infrared thermal images transferred to the information processing apparatus 4. And set the shooting interval of the infrared thermo camera 2. The information processing apparatus 4 analyzes the acquired infrared thermal image and diagnoses the soundness of the paved road 9. Further, the information processing apparatus 4 exemplified in the present embodiment calculates the latitude and longitude of each position on the paved road 9 in the infrared thermal image for each pixel based on the acquired position information of the vehicle 5. The latitude and longitude information calculated for each pixel can be used, for example, to identify the same damage between infrared thermal images having different diagnosis times in the progress status diagnosis process.

FIG. 2 is a block diagram showing an example of the functional configuration of the information processing apparatus according to the embodiment.

As shown in FIG. 2, the information processing apparatus 4 of the infrared automatic thermal analysis diagnostic system 1 according to the present embodiment includes, for example, a transmission / reception unit 400, a control unit 410, an input unit 420, a display unit 430, and a storage unit 440. ..

The transmission / reception unit 400 transmits / receives various information between the information processing device 4 and the external device connected to the information processing device 4. The transmission / reception unit 400 receives the infrared thermal image transferred from the infrared thermo camera 2 to the information processing device 4 and the position information transferred from the GPS receiver 3 to the information processing device 4. Further, the transmission / reception unit 400 transmits an infrared thermal image, position information, a diagnosis result, and the like to, for example, a server device (for example, the server device 12 in FIG. 4) connected to the information processing device 4 via a network. can do.

The control unit 410 performs various processes including a process of controlling the operation of the information processing apparatus 4. The control unit 410 analyzes the infrared thermal image and performs a process of diagnosing the soundness of the paved road 9. The process of diagnosing the soundness includes, for example, the above-mentioned individual diagnostic process and the progress diagnosis process. Further, the control unit 410 performs a process of calculating the position (latitude and longitude) of each position of the paved road 9 on the earth in the infrared thermal image for each pixel based on the position information of the vehicle 5. The control unit 410 capable of performing these processes includes, for example, an individual diagnosis unit 411, a point cloud coordinate derivation unit 412, a comparison unit 413, and a verification unit 414.

The individual diagnosis unit 411 performs a process of diagnosing the presence or absence of damage and the damage level of the paved road 9 using a set of infrared thermal images taken for one diagnosis of the paved road 9. The individual diagnosis unit 411 estimates the temperature of a healthy part based on the temperature distribution of the part of the paved road 9 to be diagnosed for each infrared thermal image, and the estimated temperature (hereinafter, "estimated healthy temperature in the image"). The presence or absence of damage and the damage level of the paved road 9 are diagnosed based on the temperature distribution of the portion of the paved road 9 to be diagnosed. Specific examples of the processing performed by the individual diagnosis unit 411 will be described later with reference to FIG.

The point cloud coordinate derivation unit 412 derives the point cloud coordinates that associate the pixels of the infrared thermal image with the position on the paved road 9 based on the position information of the vehicle 5. The point group coordinates are on the actual paved road 9 corresponding to each position (each pixel) of the paved road 9 in the infrared thermal image represented by a predetermined coordinate system set in the real space where the paved road 9 exists. The position of. When deriving the point cloud coordinates based on the position information from the GPS receiver 3 described above, the coordinate system set in the real space is, for example, a geographic coordinate system in which the position on the paved road 9 is represented by the latitude and longitude of the earth. do. The point cloud coordinate derivation unit 412 calculates, for example, the shooting direction of the infrared thermo camera 2 with respect to a predetermined reference direction such as true north at the time of shooting an infrared thermal image based on the position information of the vehicle 5. Further, the point cloud coordinate derivation unit 412 obtains the point cloud coordinates based on the angle between the reference direction and the shooting direction and the correspondence between the position in the shooting range of the infrared thermo camera 2 and the pixels in the infrared thermal image. calculate.

The comparison unit 413 compares a plurality of sets of infrared thermal images taken by a plurality of diagnoses and searches for the same damage between infrared thermal images having different diagnosis times. The comparison unit 413 identifies the position on the paved road 9 by the point cloud coordinates for each damage detected from the infrared thermal image taken in one diagnosis, and includes the position on the paved road 9. Extract the infrared thermal image taken at another diagnostic time. After that, the comparison unit 413 searches within a predetermined partial region centered on the damage position specified by the extracted infrared thermal image and the point cloud coordinates, and determines the presence or absence of the same damage. The temperature information of the infrared thermal image is used to determine the presence or absence of the same damage. Specific examples of the processing performed by the comparison unit 413 (hereinafter referred to as “continuous temperature comparison processing”) will be described later with reference to FIGS. 9 to 15.

The verification unit 414 narrows down the damaged region for each damage detected from the infrared thermal image, and performs a specific temperature region verification based on the temperature difference between the temperature of each pixel in the damaged region and the estimated healthy temperature in the image. The verification unit 414 of the information processing apparatus 4 exemplified in the present embodiment sets, for example, two regions having different areas centered on the damaged position in the infrared thermal image for each damage of the infrared thermal image, and the two regions are set in the infrared thermal image. The proportion of pixels in which the absolute value of the temperature difference from the estimated healthy temperature in the image is equal to or greater than a predetermined threshold in each region is derived. Specific examples of the processing performed by the verification unit 414 according to the present embodiment (hereinafter referred to as “specific temperature region verification processing”) will be described later with reference to FIGS. 16 and 17.

The input unit 420 receives input of various information related to the operation of the information processing apparatus 4. The display unit 430 visualizes and displays various information such as an infrared thermal image, position information, and analysis and diagnosis results. The storage unit 440 stores various information including infrared thermal images, position information, and analysis and diagnosis results.

The information processing device 4 according to the present embodiment may be a dedicated device in which dedicated hardware for carrying out the functions of each unit (functional block) of the control unit 410 illustrated in FIG. 2 is combined, and may be described later. As such, it may be a computer that executes programs for analysis and diagnosis.

The information processing apparatus 4 according to the present embodiment displays the result of the specific temperature region verification by the verification unit 414 on the display unit 430 together with the infrared thermal image, so that the analyst can know the progress of the damage detected from the infrared thermal image. Can be presented. The verification unit 414 performs a specific temperature region verification using the estimated healthy temperature in the image estimated by the individual diagnosis unit 411. Further, in the information processing apparatus 4 according to the present embodiment, the comparison unit 413 identifies the same damage of a plurality of infrared thermal images having different diagnosis times, and the damage progresses based on the change amount (change with time) of the same damage. The situation can be presented to the analyst. The comparison unit 413 uses the point cloud coordinates derived by the point cloud coordinate derivation unit 412 (that is, the correspondence between the pixels in the infrared thermal image and the actual position on the paved road 9) of a plurality of infrared thermal images. Identify the same damage. Therefore, first, the process performed by the individual diagnosis unit 411 and the point cloud coordinate derivation unit 412 (hereinafter referred to as "individual diagnosis process") will be described.

FIG. 3 is a flowchart illustrating an example of the individual diagnosis process.

When diagnosing the soundness of the paved road 9 by using the infrared automatic heat analysis diagnosis system 1 of the present embodiment, the vehicle 5 on which the infrared automatic heat analysis diagnosis system 1 is installed is driven on the paved road 9 and is carried on the paved road. The infrared thermal image of 9 and the position information of the vehicle 5 (infrared thermo camera 2) when the infrared thermal image is taken are acquired and stored in the information processing apparatus 4. At this time, the vehicle 5 is driven at a substantially constant speed, and an infrared thermal image is taken and position information is acquired at a time interval of traveling a predetermined distance (for example, 5 m) derived based on the speed of the vehicle 5. , Stored in the information processing device 4. The information processing apparatus 4 performs the individual diagnostic processing illustrated in FIG. 3 for each acquired infrared thermal image.

In the individual diagnosis process, the information processing apparatus 4 first sets a plurality of blocks in the infrared thermal image and derives information on the temperature distribution for each block (step S51). Step S51 is performed by the individual diagnosis unit 411 of the control unit 410. The individual diagnosis unit 411 divides the area to be diagnosed in the nth infrared thermal image, which is the target of analysis and diagnosis, into a plurality of blocks, and for each block, various information (blocks) regarding the temperature distribution in the block. (Inside information) is derived. The information derived by the individual diagnosis unit 411 includes the estimated healthy temperature in the block calculated based on the temperature distribution in the block and the information indicating the degree of temperature variation in the block. The individual diagnosis unit 411 calculates, for example, the average temperature in the block as the estimated healthy temperature in the block, and calculates the maximum temperature, the minimum temperature, the standard deviation, and the standard error as information indicating the degree of temperature variation.

Next, the information processing apparatus 4 derives an estimated value (estimated healthy temperature in the image) of the healthy portion of the paved road 9 in the infrared thermal image based on the information derived from each block (step S52). .. Step S52 is performed by the individual diagnosis unit 411. The individual diagnosis unit 411 derives the estimated healthy temperature in the image based on the estimated healthy temperature in the block of each block and the information indicating the degree of variation in the temperature. For example, the individual diagnosis unit 411 sets a predetermined temperature range within the temperature range from the lowest average temperature to the highest average temperature based on the average temperature of each block derived as the estimated healthy temperature in the block, and the average temperature is the average temperature. Extract blocks that are within a predetermined temperature range. After that, the individual diagnosis unit 411 sets the average temperature of the extracted blocks, for example, the block having the smallest degree of temperature variation and the high stability of the temperature distribution as the estimated healthy temperature in the image.

Next, the information processing apparatus 4 diagnoses the presence or absence of damage and the damage level for each block based on the estimated healthy temperature in the image and the information derived for each block (step S53). Step S53 is performed by the individual diagnosis unit 411. The individual diagnosis unit 411 is a part of the paved road 9 in the block based on the information indicating the temperature difference between the estimated healthy temperature in the block and the estimated healthy temperature in the image and the degree of temperature variation for each block. Evaluate the damage level. In step S53, the diagnosis result of the damage level may be combined with the infrared thermal image and displayed.

Next, the information processing apparatus 4 derives point cloud coordinates that associate the pixels in the infrared thermal image with the positions in the unique coordinate system on the paved road 9 in the real space (step S54). Step S54 is performed by the point cloud coordinate derivation unit 412 of the control unit 410. The point group coordinate derivation unit 412 is based on the position information at the time of shooting the nth infrared thermal image and the position information at the time of shooting the n + 1th infrared thermal image, and the surface (road surface) of the paved road 9 in the real space. ), The angle of the shooting direction of the infrared thermo camera 2 at the time of shooting the nth infrared thermal image with respect to a predetermined reference direction is calculated. Further, the point group coordinate derivation unit 412 is based on the calculated angle, and the position (latitude and longitude) of the paved road 9 in the geographic coordinate system corresponding to each position of the paved road 9 in the nth infrared thermal image. ) Is calculated for each pixel.

When the processing of steps S51 to S54 is completed, the information processing apparatus 4 stores the nth infrared thermal image and position information in association with the processing result in the storage unit 440 (step S55), and stores the nth infrared ray. The individual diagnostic process for processing the thermal image is completed.

The information processing apparatus 4 performs the processes of steps S51 to S55 for all the sets of the infrared thermal image and the position information that are the targets of the individual diagnostic process. The information processing apparatus 4 may pipeline the processes of steps S51 to S55.

The verification unit 414 in the information processing apparatus 4 of the present embodiment performs a specific temperature region verification using the result of the individual diagnosis process as illustrated in FIG. Further, the comparison unit 413 in the information processing apparatus 4 of the present embodiment identifies the same damage between a plurality of infrared thermal images by using the result of the individual diagnosis process as illustrated in FIG.

FIG. 4 is a block diagram illustrating an example of information stored in the storage unit. FIG. 5 is a block diagram illustrating an example of individual diagnostic data. FIG. 6 is a diagram illustrating an example of image information of individual diagnostic data. FIG. 7 is a diagram illustrating an example of analysis diagnostic information of individual diagnostic data. FIG. 8 is a diagram illustrating an example of test information of individual diagnostic data.

As illustrated in FIG. 4, the storage unit 440 of the information processing apparatus 4 includes, for example, individual diagnosis data 10A for the nth diagnosis and individual diagnosis data 10B for the n-1th diagnosis. Individual diagnostic data 10 for each of the diagnostics is stored. The individual diagnosis data 10A for the nth diagnosis is, for example, individual diagnosis data for the latest diagnosis. The individual diagnostic data 10 created by the information processing apparatus 4 performing the individual diagnostic processing is transferred to the server apparatus 12 connected to the information processing apparatus 4 via a communication network 11 such as the Internet, and is stored in the server apparatus 12. It is accumulated in the unit 1240. The server device 12 includes a transmission / reception unit 1200 that communicates with an external device such as an information processing device 4 via a communication network 11, and a control unit 1210 that controls the operation of the server device 12. The storage unit 1240 of the server device 12 is performed a plurality of times on the paved road 9 including the individual diagnosis data 10C for the first (first) diagnosis performed on the paved road 9 to be diagnosed. Individual diagnostic data 10 for each of the soundness diagnoses are accumulated. The storage unit 1240 of the server device 12 may store individual diagnostic data for the diagnostics made for each of the diagnostic sections of the plurality of different paved roads 9. The movement of the individual diagnostic data between the information processing device 4 and the server device 12 is not limited to the movement using the communication network 11, but is performed by directly connecting the information processing device 4 and the server device 12. It may be performed using a portable recording medium.

The individual diagnostic data 10 for one diagnosis includes, for example, image information 1001, analysis diagnostic information 1002, and test information 1003, as shown in FIG.

The image information 1001 includes, for example, as shown in FIG. 6, the imaged position, the temperature information of each pixel, and the road position of the infrared thermal image taken in one diagnosis and analyzed and diagnosed. .. The plurality of infrared thermal images taken in one diagnosis are each identified by the image ID. The image ID is, for example, a number indicating the order in which the images were taken. The shooting position is the position (latitude, longitude) of the vehicle 5 on the paved road 9 at the time of shooting the infrared thermal image acquired from the GPS receiver 3. The temperature information of each pixel is the temperature information in the infrared thermal image. The road position of each pixel is the point cloud coordinates derived in step S54 of the individual diagnosis process described with reference to FIG. 3, that is, the position (latitude, longitude) on the paved road 9 corresponding to each pixel.

Analytical diagnostic information 1002 includes, for example, as shown in FIG. 7, the results of analysis and diagnosis of an infrared thermal image taken in one diagnosis and analyzed and diagnosed. The image ID of the analysis diagnosis information 1002 corresponds to the image ID of the image information 1001. The block ID is information for identifying a plurality of blocks set in a region to be diagnosed in one infrared thermal image. The estimated healthy temperature in the image is an estimated value of the temperature of the healthy portion derived in step S52. The average temperature, maximum temperature, minimum temperature, standard deviation, and standard error in the block information are information on the temperature distribution for each block derived in step S51, and the damage level is the damage level evaluated in step S53. be.

The test information 1003 includes, for example, as shown in FIG. 8, the road position and the percentage of pixels of temperature anomaly for the damage detected from the infrared thermal image. Each damage detected from the infrared thermal image is identified by the damage ID. The damage ID is, for example, a number representing the order of detection. The road position is a position (latitude, longitude) on the paved road 9 corresponding to the position (pixel) of the damage in the infrared thermal image, which is specified by the above-mentioned point cloud coordinates. The ratio of temperature abnormal pixels is the ratio of pixels whose absolute value of the temperature difference from the estimated healthy temperature in the image in the first region (large region) calculated by the specific temperature region test is equal to or higher than the first threshold value. Includes the percentage of pixels in which the absolute value of the temperature difference from the estimated healthy temperature in the image within the second region (small region) is greater than or equal to the second threshold. The verification information 1003 is created, for example, by the information processing apparatus 4 performing a specific temperature region verification process described later with reference to FIG.

The individual diagnostic data 10 described with reference to FIGS. 5 to 8 is data including information that can be used by the information processing apparatus 4 of the present embodiment in the continuous temperature comparison process and the specific temperature region verification process. It's just an example. The type and storage format of the information included in the individual diagnostic data 10 can be changed as appropriate.

As described above, the information processing apparatus 4 exemplified in the present embodiment includes a comparison unit 413 that searches for and identifies the same damage between infrared thermal images having different diagnosis times. The comparison unit 413 performs continuous temperature comparison processing as illustrated in FIG. 9 by using, for example, the image information 1001 and the analysis diagnosis information 1002 included in the individual diagnosis data 10 having different diagnosis times.

FIG. 9 is a flowchart illustrating an example of the continuous temperature comparison process according to the embodiment. The comparison unit 413 of the control unit 410 selects, for example, a damage from the infrared thermal image Pt of the first diagnosis time to be the target of the diagnosis of the progress of the damage, and searches for the same damage as the damage. After the diagnosis times are set, the continuous temperature comparison process illustrated in FIG. 9 is performed. For example, the analyst operates the input unit 420 to specify and select the pixels in the infrared thermal image Pt displayed on the display unit 430 for the damage in the infrared thermal image Pt. The second diagnosis may be automatically set to, for example, the diagnosis immediately before the first diagnosis. Further, the number of diagnosis times for searching for the same damage is not limited to one time, and may be multiple times.

First, the comparison unit 413 reads out the position of the damage on the paved road 9 in the infrared thermal image Pt of the first diagnosis (step S11). The comparison unit 413 refers to the image information 1001 (see FIG. 6) in the individual diagnosis data 10 of the first diagnosis (for example, the nth), and the position (latitude, longitude) of the damaged on the paved road 9. Is read. The process of step S11 may be performed, for example, at the stage where damage (pixels) is selected from the infrared thermal image Pt.

Next, the comparison unit 413 searches for an infrared thermal image Pc including the same position in the second diagnosis round (for example, the n-1th round) based on the read-out damage position (step S12), and the infrared thermal image. It is determined whether or not there is Pc (step S13). In step S12, the comparison unit 413 searches for a road position in the image information 1001 in the individual diagnosis data 10 of the second diagnosis time, and matches or substantially matches the position (latitude, longitude) of the damage read out in step S11. It is determined whether or not there is an infrared thermal image Pc containing pixels associated with the road position. At this time, for example, by narrowing the search range of the infrared thermal image Pc in the second diagnostic round based on the imaging position of the infrared thermal image Pt including the damage in the first diagnostic round, the processing in step S12 can be performed in a short time. Can be done efficiently. When there is no infrared thermal image Pc (step S13; NO), the comparison unit 413 treats the damage to be processed as a new damage (step S14), and displays the search result on the display unit 430 (step S18). ), End the continuous temperature comparison process. In this case, in step S18, the comparison unit 413 includes infrared rays including the same road position as the damaged position in the infrared thermal image Pt of the first diagnostic round in the infrared thermal image taken in the second diagnostic round. Information indicating that there is no thermal image Pc is displayed on the display unit 430.

When the infrared thermal image Pc is present (step S13; YES), the comparison unit 413 then sets the infrared thermal image within a predetermined search range including the position corresponding to the damage of the infrared thermal image Pt in the infrared thermal image Pc. Damage is searched for based on the temperature information of (step S15), and it is determined whether or not there is damage satisfying the same damage condition within the search range (step S16). For example, the comparison unit 413 sets a search range of a predetermined shape and dimension centered on the pixel associated with the damaged position (road position) of the infrared thermal image Pt, and sets the temperature information of the pixel within the search range. Based on this, the same damage as the damage of the infrared thermal image Pt is searched for. In the comparison unit 413, for example, a pixel having the same magnitude relationship between the estimated healthy temperature in the image and the temperature of the pixel and having the largest absolute value of the temperature difference within the search range is regarded as a damage satisfying the same damage condition. do. When there is no damage satisfying the same damage condition (step S16; NO), the comparison unit 413 treats the damage to be processed as a new damage (step S14), and displays the search result on the display unit 430. (Step S18), the continuous temperature comparison process is completed. In this case, in step S18, the comparison unit 413, for example, damages the infrared thermal image Pt of the first diagnosis, the infrared thermal image Pc of the second diagnosis, and the infrared thermal image Pt in the infrared thermal image Pc. Information indicating the same road position as the position is displayed on the display unit 430. By making such a display, the analyst can easily recognize (understand) that the damage in the infrared thermal image Pt selected as the processing target is the damage detected for the first time in the first diagnosis. be able to. In addition, the analyst determines the period from the second diagnosis to the first diagnosis and the characteristics of the damage in the infrared thermal image Pt (for example, the size, shape, temperature difference from the surroundings of the damage, etc.). Based on this, the progress of the damage can be easily diagnosed.

When there is damage satisfying the same damage condition (step S16; YES), the comparison unit 413 determines the damage of the infrared thermal image Pt of the first diagnosis and the damage of the infrared thermal image Pc of the second diagnosis. The association (step S17), the search result is displayed on the display unit 430 (step S18), and the continuous temperature comparison process is completed. In this case, in step S18, the comparison unit 413, for example, damages the infrared thermal image Pt of the first diagnosis, the infrared thermal image Pc of the second diagnosis, and the infrared thermal image Pt in the infrared thermal image Pc. Information indicating the same road position as the position is displayed on the display unit 430. By making such a display, the analyst can easily determine that the damage in the infrared thermal image Pt selected for processing is the damage detected in the second diagnosis (past diagnosis). Can be recognized (understood). The analyst also sees changes in the characteristics of the damage (eg, size, shape, temperature difference from the surroundings of the damage, etc.) between the second and first diagnostics and the infrared thermal image. Based on the above, the progress of the damage can be easily diagnosed.

In addition, for example, after a plurality of damages are selected (designated) from one or more infrared thermal images of the first diagnosis, the comparison unit 413 performs continuous temperature comparison processing (steps S11 to S11) for each of the plurality of damages. It may be possible to carry out S18) continuously. In this case, the comparison unit 413 may, for example, pipeline the processes of steps S11 to S18.

As described above, in the information processing apparatus 4 of the present embodiment, the pixels of the infrared thermal image are associated with the position on the paved road 9 in a specific coordinate system (latitude, longitude) set for the paved road 9. It is possible to automatically identify the same damage between infrared thermal images with different diagnosis times by using the pixel information. Here, FIGS. 10 to 15 show the method of associating the pixel with the position on the paved road 9 (the method of deriving the point cloud coordinates by the point cloud coordinate deriving unit 412) and the method of searching for the same damage between the infrared thermal images. It will be explained briefly with reference.

FIG. 10 is a diagram illustrating a correspondence relationship between a shooting area of an infrared thermal image on an actual paved road and a position in the infrared thermal image. FIG. 11 is a diagram illustrating an example of damage detected from an infrared thermal image. FIG. 12 is a diagram illustrating an example of the relationship between the moving direction of the vehicle and the reference direction. FIG. 13 is a diagram illustrating an example of a method for deriving the point cloud coordinates. FIG. 14 is a diagram illustrating an example of a shooting range of an infrared thermal image including the same position on the road. FIG. 15 is a diagram illustrating an example of a method for searching for the same damage between thermal infrared images having different diagnosis times.

When diagnosing the soundness of the paved road 9 by the infrared automatic thermal analysis diagnostic system 1 of the present embodiment, the vehicle on the paved road 9 is used by the infrared thermo camera 2 installed above the vehicle 5 as illustrated in FIG. When the photographing area R in front of 5 is photographed, the photographing area R on the surface (road surface) of the paved road 9 becomes, for example, a substantially trapezoidal area R (m) as shown in FIG. In this case, as illustrated in FIG. 10, the rectangular infrared thermal image 15 of U × V pixels is an image obtained by photographing a portion of a substantially trapezoidal photographing area R (m) on an actual paved road 9. Therefore, the pixels (0,0), (U-1,0), (0,V-1), and (U-1, V-1) at the four corners of the infrared thermal image 15 are trapezoidal images, respectively. Corresponds to the vertices RF1 (m), RF2 (m), RN1 (m), and RN2 (m) in the region R (m). Further, any pixel (u, v) excluding the pixels at the four corners in the infrared thermal image 15 corresponds to an arbitrary point Q in the photographing region R (m).

That is, the rectangular region Rdig in the photographing region R (m) of the paved road 9 is a substantially trapezoidal region 16 in the infrared thermal image 15. When the above-mentioned individual diagnosis process is performed in the information processing apparatus 4 of the present embodiment, the substantially trapezoidal region 16 in the infrared thermal image 15 corresponding to the region Rdig on the paved road 9 is divided into a plurality of blocks. .. In this case, when the region Rdig on the paved road 9 is divided into a plurality of blocks having the same shape, the corresponding block in the substantially trapezoidal region 16 in the infrared thermal image 15 becomes smaller as the distance from the lower side increases. Therefore, when performing the individual diagnosis process, it is preferable to set the number of pixels in each block to be the number of pixels that can calculate a significant average temperature and temperature variation. In the individual diagnostic process described with reference to FIG. 3, the process of steps S51 to S53 is performed for each block in the region 16 divided in this way to diagnose the presence or absence of damage and the damage level.

An example of the infrared thermal image 15 taken by the infrared thermo camera 2 is shown in FIG. In the infrared thermal image 15 illustrated in FIG. 11, the temperature of each pixel is represented by a gray scale in which the pixel with the highest temperature is white and the pixel with the lowest temperature is black. The portion 17A of the region 16 to be diagnosed in the infrared image 15 of FIG. 11 includes a partial region having a higher temperature than the other portion of the paved road 9. On the other hand, the partial region 17B of the region 16 to be diagnosed in the infrared thermal image 15 of FIG. 11 includes a partial region having a lower temperature than the other portion of the paved road 9. It is considered that the partial region where the temperature is higher than the other portion and the partial region where the temperature is lower than the other parts of the paved road 9 are damaged parts. It is desirable to deal with the damaged part at an appropriate time before it becomes severe. The information processing apparatus 4 of the present embodiment will be described with reference to FIG. 9, for example, by designating pixels (ua, va) indicating the positions of damage in the partial region 17A of the infrared thermal image 15 illustrated in FIG. By performing the continuous temperature comparison processing, it is possible to diagnose how much the damage has progressed as compared with the case where the damage is detected from the infrared thermal images taken in the past diagnosis times. In the continuous temperature comparison process, the same damage in the infrared thermal image taken in the past diagnosis times is searched by using the correspondence relationship between the designated pixel (ua, va) and the position on the paved road 9.

The correspondence between the pixels of the infrared thermal image used in the information processing apparatus 4 of the present embodiment and the position (latitude, longitude) on the paved road 9 is the position acquired by using the GPS receiver 3 at the time of taking the infrared thermal image. It is derived by the point group coordinate derivation unit 412 based on the information (latitude, longitude). The individual position information acquired by the information processing apparatus 4 from the GPS receiver 3 is information indicating the position of the vehicle 5 (infrared thermo camera 2) on the earth, and is from the position specified by the position information G (m). It does not include information indicating which direction was taken. Therefore, it is not possible to derive the latitude and longitude of each point in the photographing region R (m) of the paved road 9 only by the position information G (m) when the mth infrared thermal image 15 is photographed. Therefore, the point group coordinate derivation unit 412 according to the present embodiment is based on, for example, the angle between the reference direction (for example, the direction of the true north) in the geographic coordinate system set on the paved road 9 and the moving direction of the vehicle 5. Then, the latitude and longitude of each point in the shooting range R (m) when the mth infrared thermal image 15 is shot are derived.

For example, as shown in FIG. 12, in the infrared automatic thermal analysis diagnosis system 1 of the present embodiment, every time the vehicle 5 moves by a predetermined distance Lcap (for example, about 5 m), the infrared thermal image 15 and the position information are displayed. Acquire G (m-1), G (m), and G (m + 1). At this time, since the shooting interval of the infrared thermal image 15 is, for example, about 0.2 seconds to 0.3 seconds, as illustrated in FIG. 12, the shooting center of the infrared thermo camera 2 projected on the paved road 9 The direction DVC can be approximated to the moving direction of the vehicle 5 derived based on the position information G (m-1), G (m), and G (m + 1) at the time of shooting the infrared thermal image 15. Therefore, the point cloud coordinate derivation unit 412 uses, for example, the angles θ1 and θ2 in the moving direction of the vehicle 5 with respect to the reference direction in the coordinate system used to specify the position of each point on the paved road 9, and the photographing area. The position of each point in R (m) is derived. When the position information G (m) acquired by the GPS receiver 3 is information represented by latitude and longitude, the reference direction is, for example, the direction of true north.

In order to derive the position of each point in the photographing region R (m) by using the angle of the moving direction of the vehicle 5 with respect to the reference direction (true north direction), the point group coordinate derivation unit 412 may be used, for example, in FIG. As illustrated in the above, the positions (latitude and longitude) of each point in the shooting region (hereinafter referred to as “reference shooting region”) Rref when the direction DVC of the shooting center of the infrared thermo camera 2 is the reference direction are derived. In FIG. 13, the reference imaging region Rref when the direction DVC of the imaging center is set as the reference direction is shown as a trapezoid of dotted lines in a two-dimensional coordinate system having latitude and longitude as the Y-axis and the X-axis, respectively. At this time, the positions (latitude and longitude) of each point in the reference shooting area Rref are the position information G (m) indicating the position of the vehicle 5 (infrared thermo camera 2) at the time of shooting and each point from the position of the vehicle 5. It can be calculated using a well-known calculation method based on the direction and distance to.

After calculating the position of each point in the reference photographing area Rref, the point group coordinate derivation unit 412 actually photographs the mth infrared thermal image in the reference direction (+ Y direction) as shown in FIG. Using the angle θ2 with the stretching direction DVC (+ Y'direction) of the imaging center at the time of this, coordinate transformation is performed to rotate the position of each point in the reference imaging region Rref on the two-dimensional plane. The coordinate transformation can be performed using, for example, a well-known transformation matrix. By this coordinate conversion, for example, the vertices RRF1, RRF2, RRN1 and RRN2 of the reference photographing region Rref are rotated by an angle θ2 with the point specified by the position information G (m) as the rotation center, respectively, at the position RF1 (m). ), RF2 (m), RN1 (m), and RN2 (m). Further, for example, the point QR in the reference photographing area Rref is converted into the position Q. As a result, the latitude and longitude of each point in the imaging region R (m) when the mth infrared thermal image is captured can be obtained. Therefore, as described with reference to FIG. 10, the latitude and longitude of each point in the photographing region R (m) corresponding to each position of the paved road 9 in the mth infrared thermal image 15 are set pixel by pixel. Can be derived from. The latitude and longitude information corresponding to each position (each pixel) of the paved road 9 in the derived infrared thermal image 15 is stored in the storage unit 440 in a format such as the image information 1001 illustrated in FIG. 6, for example. ..

In the conventional analytical diagnosis method using an infrared thermal image, for example, an analyst observes an infrared thermal image to diagnose the presence or absence of damage and the progress of damage, so that the paved road 9 in the infrared thermal image is diagnosed. It was difficult to derive the latitude and longitude corresponding to each position (each pixel). Therefore, when identifying a damaged part of the actual paved road 9 based on the result of analysis and diagnosis, for example, an infrared thermal image, an image taken by a visible light camera when taking an infrared thermal image, or the like is used. It was difficult to efficiently identify the position and range of the damaged part because it was specified by reliance.

On the other hand, the information processing apparatus 4 of the present embodiment stores the point cloud coordinates indicating the latitude and longitude corresponding to each position (each pixel) in the infrared thermal image 15 in the storage unit 440 as a part of the image information 1001. Let me. Therefore, by referring to the point cloud coordinates of the image information 1001, the latitude and longitude of the damaged portion of the paved road 9 in the infrared thermal image 15 can be easily specified, and the actual damage to the paved road 9 can be specified. It is possible to efficiently identify the position and range of a certain part.

Further, when an infrared thermal image including a specific position on the paved road 9 is photographed, as illustrated in FIG. 14, the imaging region R _n-1 (for example, the n-1th diagnosis) in a certain diagnosis (for example, the n-1th diagnosis) is taken. There is a discrepancy between m) and the imaging region R _n (m) in the next diagnosis (for example, the nth diagnosis). In such a case, the position of the pixel in the infrared thermal image taken by the n-1st diagnosis corresponding to the position on the paved road 9 (LA (1), LO (1)) and the nth diagnosis. The position of the pixel in the captured infrared thermal image is different. Therefore, for example, it is difficult to compare and observe two infrared thermal images to identify the same damage. On the other hand, when the point cloud coordinates are used, the positions of the pixels in the infrared thermal image taken in the n-1th diagnosis, which correspond to the positions on the paved road 9 (LA (1), LO (1)), The positions of the pixels in the infrared thermal image taken by the nth diagnosis can be easily specified.

When the point cloud coordinates are derived based on the position information from the GPS receiver 3, for example, an error in the position (latitude and longitude) according to the accuracy of the GPS receiver 3 occurs. Therefore, in the information processing apparatus 4 (comparison unit 413) of the present embodiment, as described above, a predetermined position including a position specified based on the point cloud coordinates in the infrared thermal image Pc of the second diagnosis time is included. Within the search range, the same damage as the damage of the infrared thermal image Pt in the first diagnosis is searched for (step S15).

For example, in FIG. 15, the pixels corresponding to the road positions (LA (1), LO (1)) in the point cloud coordinates of the infrared thermal image 15 taken in the nth diagnosis are (ua, va). The case where the pixel corresponding to the road position (LA (1), LO (1)) by the point cloud coordinates of the infrared thermal image 15 taken in the n-1th diagnosis is (ub, vb) is shown. At this time, for example, in the infrared thermal image 15 taken in the n-1th diagnosis, the pixel actually corresponding to the road position (LA (1), LO (1)) was (uc, vc). do. In this case, the road position (LA (1), LO (1)) is the damaged position, and the pixel corresponding to the damaged position in the infrared thermal image 15 taken in the n-1th diagnosis is (ub, vb). However, if the progress of damage is derived, it may not be possible to derive an appropriate progress.

Therefore, in the information processing apparatus 4 of the present embodiment, as shown in FIG. 15, within the search range 18 centered on the pixels (ub, vb) in the infrared thermal image 15 taken in the n-1th diagnosis. , Search for the same damage using temperature information. As a result, it is possible to accurately identify the same damage between infrared thermal images having different diagnosis times, and it is possible to more appropriately diagnose (understand) the progress of the damage. The shape and size of the search range 18 are arbitrary, and can be set based on, for example, the accuracy of the position information used for deriving the point cloud coordinates.

That is, in the information processing apparatus 4 of the present embodiment, the infrared heat of the first diagnosis time in the infrared heat image Pc of the second diagnosis time, which is specified based on the position on the paved road 9 associated with the pixel. By searching for the presence or absence of the same damage within a predetermined search range including the position (pixel) corresponding to the damage of the image Pt, the damaged part of the paved road 9 in the infrared thermal image Pt and the damaged portion in the infrared thermal image Pc. It is possible to identify the damaged part with high accuracy. Therefore, for example, together with the infrared thermal image Pt, the infrared thermal image Pc and the information indicating the same road position as the damaged position of the infrared thermal image Pt in the infrared thermal image Pc are displayed on the display unit 430 for diagnosis. It is possible to appropriately diagnose the progress of the damage by comparing a plurality of infrared thermal images containing the same damage at different times.

Further, in the information processing apparatus 4 of the present embodiment, as described above, the damaged area is narrowed down for each damage detected from the infrared thermal image, and the temperature of each pixel in the damaged area and the estimated healthy temperature in the image are set. It includes a verification unit 414 that performs a specific temperature region verification based on a temperature difference. The verification unit 414 performs continuous temperature comparison processing as illustrated in FIG. 16 by using, for example, the analysis diagnosis information 1002 included in the individual diagnosis data 10.

FIG. 16 is a flowchart illustrating an example of the specific temperature region verification process according to the embodiment. For example, when the analyst operates the input unit 420 to specify the position (pixel) of the damage in the infrared thermal image displayed on the display unit 430, the verification unit 414 performs the specific temperature verification process illustrated in FIG. ..

First, the verification unit 414 sets a first region and a second region having different areas centered on the damage position in the infrared thermal image Pt including the damage to be processed (step S21). The first region and the second region are set, for example, so that the area of the first region is larger than the area of the second region. The first region and the second region can each have an arbitrary shape, and may have a similar shape or a non-similar shape. For example, when each of the first region and the second region is set in a rhombus centered on the damaged position, the first region is set so that the area of the first region is four times the area of the second region. Area and a second area can be set.

Next, the verification unit 414 derives the ratio R1 of the pixels in the first region whose absolute value of the temperature difference from the estimated healthy temperature in the image is ΔT1 (> 0) or more (step S22). , The ratio R2 of the pixels in which the absolute value of the temperature difference from the estimated healthy temperature in the image among the pixels in the second region is ΔT2 (> ΔT1) is derived (step S23). The combination of the threshold temperatures ΔT1 and ΔT2 is arbitrary, and can be, for example, ΔT1 = 1 ° C. and ΔT2 = 2 ° C. The processes of steps S22 and S23 may be performed in reverse order or in parallel.

Next, the verification unit 414 causes the display unit 430 to display information indicating the derived pixel ratios R1 and R2 (step S24), and records the derived pixel ratios R1 and R2 in association with the damage position (step). S25) The specific temperature verification process for one damage is completed. In step S24, the verification unit 414 has, for example, that the absolute value of the temperature difference from the estimated healthy temperature in the image among the pixels in the region that is in the first region and does not overlap with the second region is ΔT1 or more. A pixel is displayed in the first color, and a pixel whose absolute value of the temperature difference from the image estimated healthy temperature in the second region is ΔT2 or more is displayed in the second color. The processes of steps S24 and S25 may be performed in reverse order or in parallel.

In addition, for example, after a plurality of damages are selected (designated) from one or more infrared thermal images, the verification unit 414 continuously performs a specific temperature region verification process (steps S21 to S25) for each of the plurality of damages. It may be possible to do so. In this case, the verification unit 414 may, for example, pipeline the processes of steps S21 to S23 and the processes of steps S24 and S25.

On the other hand, the information processing apparatus 4 (verification unit 414) of the present embodiment is specified by using the estimated healthy temperature in the image derived based on the temperature distribution given by the temperature information of each pixel in the infrared thermal image 15. Perform temperature region verification processing. Since the estimated healthy temperature in the image used in this specific temperature region verification process uses the temperature information of the infrared thermal image 15, the objectivity, quantitativeness, and result identity are high. Therefore, by performing the specific temperature region verification process described with reference to FIG. 16, the objectivity, quantitativeness, and result identity of the damaged region can be improved, and the progress of damage can be appropriately determined. Can be diagnosed.

FIG. 17 is a diagram illustrating an example of a first region and a second region set in the specific temperature region verification process. FIG. 17 shows an example of the first region 19A and the second region 19B when the specific temperature region verification process is performed on the damage 20 in the partial region 17A in the infrared thermal image 15 exemplified in FIG. There is. Note that FIG. 17 shows a partial image 151 of the infrared thermal image 15 exemplified in FIG. 11 in which the damage 20 and the surrounding area thereof are enlarged. When the pixel indicating the position of the damage 20 is (ua, va), in the specific temperature region verification process, for example, as shown in FIG. 17, the first region of the rhombus centered on the pixel (ua, va). 19A and the second area 19B are set. In the diamond-shaped first region 19A and the second region 19B exemplified in FIG. 17, the length L1 of one side of the first region 19A is twice the length L2 of one side of the second region 19B. It is set.

In the example shown in FIG. 17, the damage 20 extends to the outside of the second region 19A. In the case of such damage 20, the pixels included in the damage 20 in the annular region in the first region 19A and outside the second region 19B have a color representing the temperature in the infrared thermal image 15. Displayed in a different first color. Further, the pixels included in the damage 20 in the second region 19B are displayed in a color representing the temperature in the infrared thermal image 15 and a second color different from the first color. Therefore, for example, it can be said that the information displayed on the display unit 430 by step S24 of the specific temperature region verification process objectively and quantitatively indicates the range of the damage 20. Further, since the information displayed on the display unit 430 in step S24 of the specific temperature region verification process is information derived (calculated) using the temperature information of the infrared thermal image 15, the individual diagnostic criteria for each analyst is individual. It can be said that the information has very high result identity without being affected by differences.

As described above, the relationship between the shapes and areas of the first region 19A and the second region 19B is arbitrary and is not limited to the specific shape and area. The first region 19A and the second region 19B are, for example, an isotropic region centered on the damaged position on the paved road 9 (for example, a circular region centered on the damaged position, a polygonal region, etc.). It can also be set to the corresponding shape.

As described above, in the information processing apparatus 4 of the present embodiment, the infrared thermal image having different diagnosis times is used by using the point group coordinates that associate the pixels of the infrared thermal image with the unique position information on the paved road 9. It is possible to identify the same damage between the two, and to objectively and quantitatively diagnose (understand) the progress of the damage. Further, in the information processing apparatus 4 of the present embodiment, a first region and a second region centered on the damaged position are set in the infrared thermal image, and the estimated healthy temperature in the image in the first region is set. By deriving the ratio R1 of the pixels whose absolute value of the temperature difference is ΔT1 or more and the ratio R2 of the pixels whose absolute value of the temperature difference from the estimated healthy temperature in the image in the second region is ΔT2 or more. , It is possible to objectively and quantitatively diagnose (understand) the progress of the damage.

The above-described embodiment shows a specific example for facilitating the understanding of the invention, and the present invention is not limited to the above-mentioned embodiment. The information processing device 4 according to the present invention, the system including the information processing device 4, and the method and program for the processing performed by the information processing device 4 are subject to various modifications and changes without departing from the description of the claims. It is possible.

For example, in the information processing apparatus 4, the individual diagnosis unit 411 of the control units 410 illustrated in FIG. 2 may be omitted. Further, when the image information 1001 including the point cloud coordinates as illustrated in FIG. 6 can be acquired, the individual diagnosis unit 411 and the point cloud coordinate derivation unit 412 may be omitted. Further, the information processing apparatus 4 may include one functional block in which the comparison unit 413 and the verification unit 414 are integrated, or includes only one of the comparison unit 413 and the verification unit 414. It may be a thing.

Further, for example, the information processing apparatus 4 is not limited to a dedicated device in which dedicated hardware for carrying out the functions of each unit (functional block) of the control unit 410 as illustrated in FIG. 2 is combined, and FIG. 9 is shown. It may be a computer that executes a program including one or both of the continuous temperature comparison process as described with reference and the specific temperature region verification process as described with reference to FIG.

FIG. 18 is a diagram illustrating a hardware configuration example of a computer.

The computer 30 illustrated in FIG. 18 includes a processor 31, a main storage device 32, an auxiliary storage device 33, an input device 34, a display device 35, an input / output interface 36, a communication device 37, and a medium drive device 38. These hardware of the computer 30 are interconnected by a bus 39.

The processor 31 is, for example, a CPU (Central Processing Unit). The main storage device 32 includes a ROM (Read Only Memory) and a RAM (Random Access Memory). The processor 31 controls the overall operation of the computer 30, for example, by executing a program loaded in the main storage device 32. The processor 31 can execute various programs such as a program included in an OS (Operating System). The program that can be executed by the processor 31 can execute a program that includes either or both of the continuous temperature comparison process described with reference to FIG. 9 and the specific temperature region verification process described with reference to FIG. .. The main storage device 32 stores a program including either or both of continuous temperature comparison processing and specific temperature region verification processing, various information referred to during execution of the program, and various information derived (calculated). be able to.

The auxiliary storage device 33 is a storage device having a larger capacity than the main storage device 32, and is, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The auxiliary storage device 33 stores a program including one or both of continuous temperature comparison processing and specific temperature region verification processing, various information referred to during execution of the program, and various derived (calculated) information. be able to.

The input device 34 is a device that performs an input operation to the computer 30 such as a keyboard and a mouse, and the display device 35 is a device that visualizes and displays various data such as a liquid crystal display. When the computer 30 is provided with a touch panel display such as a tablet computer or a smartphone, the input device 34 may include, for example, a digitizer (position detection device) arranged so as to be superimposed on the display surface of the display device 35. ..

The input / output interface 36 is a hardware interface for connecting the computer 30 and peripheral devices and the like. For example, the infrared thermo camera 2 and the GPS receiver 3 are connected to the computer 30 by the input / output interface 36.

The communication device 37 connects the computer 30 to a communication network 41 such as the Internet, and communicates with an external device such as the server device 42 via the communication network 41. The communication device 37 communicates with the server device 12 or the like via the communication network 11 by wireless communication or by wired communication using a communication cable such as a LAN (Local Area Network) cable (see FIG. 4). The server device 12 can be used, for example, to aggregate the results of analysis and diagnosis performed by the computer 30.

The medium driving device 38 accesses the portable recording medium 40, reads out the information recorded on the portable recording medium 40, writes the information to the portable recording medium 40, and the like. The portable recording medium 40 includes, for example, an optical disk, a magnetic disk, a magneto-optical disk, and a card-type semiconductor memory device. The portable recording medium 40 stores a program including one or both of continuous temperature comparison processing and specific temperature region verification processing, various information referred to during execution of the program, and various derived (calculated) information. can do.

The hardware configuration of the computer 30 that can be used as the information processing device 4 is not limited to the configuration illustrated in FIG. 18, and can be appropriately changed. The computer 30 may not include one or more of the hardware configurations exemplified in FIG. 18 (eg, the medium drive device 38). Further, the computer 30 may include hardware different from the hardware configuration illustrated in FIG.

The continuous temperature comparison process performed by the information processing apparatus 4 (computer 30) is not limited to the content and order of the processes described with reference to FIG. 9, and can be appropriately changed. Similarly, the specific temperature region verification process performed by the information processing apparatus 4 (computer 30) is not limited to the content and order of the processes described with reference to FIG. 16, and can be appropriately changed. For example, in the specific temperature region verification process, the same process as in steps S11, S12, and S15 in the continuous temperature comparison process exemplified in FIG. 9 is performed to identify an infrared thermal image containing the same damage in the past diagnosis times. It may be a process capable of outputting the result of a specific temperature region verification process or the like for the same damage of the infrared thermal image. Further, the information processing apparatus 4 (computer 30) can not only perform the continuous temperature comparison process and the specific temperature region verification process as separate processes, but also perform these two processes continuously. May be good. For example, the information processing apparatus 4 (computer 30) identifies the same damage as the damage of the infrared heat image Pt in the infrared heat image Pc by the continuous temperature comparison process, and then continues to identify the same infrared heat. It may be possible to perform a specific temperature region verification process for each of the damage of the image Pt and the damage of the infrared thermal image Pc. The information processing apparatus 4 (computer 30) capable of such processing has, for example, damage based on the result of individual specific temperature region verification processing for each of the damage of the infrared thermal image Pt and the damage of the infrared thermal image Pc. It may be possible to perform a process of diagnosing whether or not the degree has progressed.

Further, the program executed by the computer 30 used as the information processing apparatus 4 may include, for example, a program for deriving the point cloud coordinates. The program for deriving the point cloud coordinates may be a part of the individual diagnostic processing program as described with reference to FIG. 3, or the processing of steps S51 to S53 for diagnosing the presence / absence of damage and the damage level. It may be a program separate from the included program. Further, the process of deriving the point cloud coordinates may be included in, for example, a continuous temperature comparison process and a specific temperature region verification process.

Further, the information processing device 4 (computer 30) accesses an external device (for example, the server device 12 exemplified in FIG. 4), acquires individual diagnostic data stored in the storage unit of the external device, and compares the continuous temperature. Either one or both of the treatment and the specific temperature region verification treatment may be performed. That is, the present invention includes a device including a control unit that performs either or both of continuous temperature comparison processing and specific temperature region verification processing, and a device including a storage unit that stores individual diagnostic data used for the processing performed by the device. Includes a diagnostic system, which is a different device communicatively connected.

Further, the system configuration of the infrared automatic thermal analysis system 1 according to the present invention is not limited to the configuration described above, and can be appropriately changed. For example, the infrared automatic thermal analysis system 1 may include a visible light camera that photographs a paved road 9 including an imaging region R of the infrared thermo camera 2.

1 Infrared automatic thermal analysis diagnostic system 2 Infrared thermo camera 3 GPS receiver 4 Information processing device 400 Transmission / reception unit 410 Control unit 411 Individual diagnosis unit 412 Point group coordinate derivation unit 413 Comparison unit 414 Verification unit 420 Input unit 430 Display unit 440 Storage unit 5 Vehicle 6 Metal fittings 9 Paved road 10, 10A, 10B, 10C Individual diagnostic data 1001 Image information 1002 Analysis diagnostic information 1003 Verification information 11 Communication network 12 Server device 1200 Transmission / reception unit 1210 Control unit 1240 Storage unit 15 Infrared thermal image 16 Target of diagnosis Area 18 Search range 20 Damage 30 Computer 31 Processor 32 Main memory 33 Auxiliary storage 34 Input device 35 Display device 36 Input / output interface 37 Communication device 38 Media drive device 39 Bus 40 Portable recording medium 41 Communication network 42 Server device

Claims (10)

The computer
The paved road in a predetermined coordinate system set on the pixels in the infrared thermal image and the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. A continuous temperature comparison characterized by identifying the same damaged part among a plurality of infrared thermal images having different diagnosis times based on the correspondence with the above position and the temperature information of the damaged part in the infrared thermal image. Method. In the continuous temperature comparison method according to claim 1,
The computer
A second image taken in a second diagnosis before the first diagnosis, based on the position of the damaged portion on the paved road in the first infrared thermal image taken in the first diagnosis. Identify the pixel corresponding to the position on the paved road in the infrared thermal image,
The second infrared heat, which is the same as the damaged portion in the first infrared thermal image, based on the temperature information about the pixels in the predetermined search range in the second infrared thermal image including the specified pixel. A continuous temperature comparison method characterized by identifying damaged areas in an image. In the continuous temperature comparison method according to claim 2,
The computer
Of the pixels in the search range in the second infrared thermal image, the temperature of the pixel of the damaged portion in the first infrared thermal image and the soundness of the paved road estimated from the first infrared thermal image. A continuous temperature comparison method, characterized in that a pixel having the same high-low relationship with the temperature of a specific portion and having the maximum absolute value of the temperature difference is specified as the damaged portion in the second infrared thermal image. .. The computer
The estimated healthy temperature of the healthy part of the paved road estimated from the infrared thermal image of the paved road taken by the infrared thermo camera is derived.
The proportion of pixels in the first region including the damaged position in the infrared thermal image whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the pixel in the infrared thermal image. The absolute value of the temperature difference from the estimated healthy temperature among the pixels in the second region including the damaged position and smaller than the first region is greater than or equal to the second threshold value larger than the first threshold value. Calculate the pixel ratio and
A specific temperature region verification method characterized by outputting the calculated ratio of the pixels. The paved road in a predetermined coordinate system set on the pixels in the infrared thermal image and the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. It is characterized by including a control unit that identifies the same damaged part among a plurality of infrared thermal images having different diagnosis times based on the correspondence with the upper position and the temperature information of the damaged part in the infrared thermal image. Information processing device. Of the pixels in the first region including the damaged position in the infrared thermal image, the estimated healthy temperature of the healthy part of the paved road estimated from the infrared thermal image of the paved road taken by the infrared thermo camera is derived. Within the second region, which includes the proportion of pixels whose absolute value of the temperature difference from the estimated healthy temperature is equal to or greater than the first threshold value and the damaged position in the infrared thermal image, which is smaller than the first region. The ratio of the pixels whose absolute value of the temperature difference from the estimated healthy temperature is greater than or equal to the second threshold value larger than the first threshold value is calculated, and the calculated ratio of the pixels is output. , An information processing device characterized by having a control unit. On the paved road in a predetermined coordinate system set on the paved road and the pixels in the infrared thermal image of the damaged part of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. A storage unit that stores the correspondence with the position of the road and the temperature information of the damaged part in the infrared thermal image, and the storage unit.
A plurality of infrared rays having different diagnosis times based on the correspondence between the pixels in the infrared thermal image stored in the storage unit and the position on the paved road, and the temperature information of the damaged portion in the infrared thermal image. A continuous temperature comparison system comprising a control unit that identifies the same damaged part between thermal images. A storage unit that stores an infrared thermal image of a paved road taken by an infrared thermo camera and an estimated healthy temperature of a healthy part of the paved road estimated from the infrared image.
The proportion of pixels in the first region including the damaged position in the infrared thermal image whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the said in the infrared thermal image. The absolute value of the temperature difference from the estimated healthy temperature among the pixels in the second region including the damaged position and smaller than the first region is greater than or equal to the second threshold value larger than the first threshold value. A specific temperature region verification system including a control unit that calculates a pixel ratio and outputs the calculated pixel ratio. On the computer
The paved road in a predetermined coordinate system set on the pixels in the infrared thermal image and the paved road for the damaged portion of the paved road detected from the infrared thermal image of the paved road taken by the infrared thermo camera. It is characterized by executing a process of identifying the same damaged part among a plurality of infrared thermal images having different diagnosis times based on the correspondence with the upper position and the temperature information of the damaged part in the infrared thermal image. Program to do. On the computer
The estimated healthy temperature of the healthy part of the paved road estimated from the infrared thermal image of the paved road taken by the infrared thermo camera is derived.
The proportion of pixels in the first region including the damaged position in the infrared thermal image whose absolute value of the temperature difference from the estimated healthy temperature is equal to or higher than the first threshold value and the pixel in the infrared thermal image. The absolute value of the temperature difference from the estimated healthy temperature among the pixels in the second region including the damaged position and smaller than the first region is greater than or equal to the second threshold value larger than the first threshold value. Calculate the pixel ratio and
A program characterized by executing a process of outputting the calculated ratio of the pixels.

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