Image information processing device, inspection support device, and method

Abstract

To provide an image information processing apparatus configured to display a high-resolution point cloud image including a CAD difference in a practical time, an inspection support apparatus, and a method.SOLUTION: In an image information processing apparatus configured to input an image and a high-density point cloud from a camera and a laser scanner directed to a device on site to process information in an arithmetic unit of a computer device, the arithmetic unit includes functions of: a point cloud thinning unit which performs thinning on the high-density point cloud to generate a low-density point cloud; and a point cloud-image association unit which obtains point cloud-image association information obtained by integrating and arranging information on the low-density point cloud on the image. An image composed of multiple pixels includes position information and color information of the pixels on the image. The point cloud incudes position information and color information between the device and the laser scanner. The information on the low-density point cloud is integrated on the image, using position information of the image and position information of the point cloud.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an image information processing device, an inspection support device, and a method for processing image information obtained from a laser scanner. [Background technology]

[0002] In various plants and other facilities, it is common to process information obtained from cameras and scanners for the purpose of monitoring and inspection according to the respective purpose, and to reflect the results in monitoring and control.

[0003] For example, at nuclear power plants, on-site inspections are carried out to improve safety and check for discrepancies between design and construction, deterioration of equipment, etc., but there is an issue with the excessive amount of inspection work required, including on-site transportation for workers, entry procedures, etc. From the perspective of plant safety and cybersecurity, it is conceivable to carry out real-time remote inspections using cameras, IoT devices, and wireless, but this is difficult to realize.

[0004] In this regard, a system that utilizes point clouds / images measured by a laser scanner and design CAD models to perform on-site inspections in a VR space is considered to be effective in reducing inspection man-hours. For example, in Patent Document 1, regarding this technology, in order to streamline the recording of equipment inspection results, the point clouds acquired from a laser scanner are converted into images and displayed (point cloud images), supporting CAD modeling and also enabling the point cloud images and CAD models to be superimposed. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2018-10455 A Summary of the Invention [Problem to be solved by the invention]

[0006] According to Patent Document 1, it is possible to realize point cloud image display. However, in order to ensure a practical rendering processing speed, it is necessary to thin out the point cloud, which reduces the resolution of the generated point cloud image, making it inapplicable to the inspection of small objects (bolts, etc.) or parts far from the scanning position.

[0007] In addition, to compare the differences between design and construction, the point cloud must be converted into a CAD model, which requires a significant amount of modeling work to inspect using VR, except for simple shapes (such as pipe penetrations) that can be automatically converted into CAD models.

[0008] In view of the above, an object of the present invention is to provide an image information processing device, an inspection support device, and a method that are capable of displaying high-resolution point cloud images including CAD differences within a practical amount of time. [Means for solving the problem]

[0009] In view of the above, the present invention is an image information processing device which inputs images and high-density point clouds from a camera and laser scanner aimed at on-site equipment and processes the information in a calculation unit of a computer device, the calculation unit having the functions of a point cloud thinning unit which thins out the high-density point cloud to produce a low-density point cloud, and a point cloud-image linking unit which obtains point cloud-image linking information in which the low-density point cloud information is linked and arranged on an image, the image composed of multiple pixels includes position information and color information of the pixels on the image, the point cloud includes position information and color information between the equipment and the laser scanner, and the image information processing device is characterized in that the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud.

[0010] The present invention is further described as "an inspection support device comprising a camera and a laser scanner aimed at on-site equipment, an input unit for inputting images and a high-density point cloud from the camera and the laser scanner, a calculation unit for processing information from the input unit, and a display unit for displaying the processing results of the calculation unit, wherein the calculation unit has the functions of a point cloud thinning unit for thinning out a high-density point cloud to produce a low-density point cloud, and a point cloud-image linking unit for obtaining point cloud-image linking information in which information of the low-density point cloud is linked and arranged on an image, and the point cloud-image linking information is displayed on the display unit, and an image composed of a plurality of pixels includes position information and color information of pixels on the image, the point cloud includes position information and color information between the equipment and the laser scanner, and the inspection support device is characterized in that the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud."

[0011] In addition, the present invention provides an image information processing method for inputting an image and a high-density point cloud from a camera and a laser scanner aimed at an on-site device, and processing the information in a computing unit of a computer device, The calculation unit thins out the high-density point cloud to create a low-density point cloud, and obtains point cloud-image linkage information in which the low-density point cloud information is linked and arranged on the image, and the image composed of multiple pixels includes position information and color information of the pixels on the image, and the point cloud includes position information and color information between the device and the laser scanner, and the low-density point cloud information is linked on the image using the image position information and point cloud position information.

[0012] The present invention is further described as "an inspection support method which obtains images and high-density point cloud information from a camera and a laser scanner aimed at on-site equipment, processes the information, and displays the processing results, characterized in that the high-density point cloud is thinned out to form a low-density point cloud, point cloud-image linkage information is obtained in which the low-density point cloud information is linked and arranged on the image, and the point cloud-image linkage information is displayed, and an image composed of a plurality of pixels includes position information and color information of pixels on the image, the point cloud includes position information and color information between the equipment and the laser scanner, and the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud." Effect of the Invention

[0013] According to the present invention, a point cloud image including high resolution and CAD differences can be displayed within a practical time. [Brief description of the drawings]

[0014] [Figure 1] 1 is a diagram showing an example of the overall configuration of an inspection support device using an image information processing device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing an example of an environment measured by a laser scanner 11. [Diagram 3] FIG. 2 is a diagram showing an example of a high-density point group D1a obtained by measurement using a laser scanner 11. [Figure 4] FIG. 2 is a diagram showing an example of the data configuration of a point group D1a. [Diagram 5] FIG. 13 is a diagram showing an example of a low-density point group D2 obtained by thinning processing. [Figure 6] A figure showing an example of photographic data (pixels) D1b obtained by laser scanner measurement. [Figure 7] A diagram showing information about each pixel using coordinates (image coordinates) on the vertical axis Ix and the horizontal axis IY, with the upper left corner of the image as the origin. [Figure 8] FIG. 13 is a diagram illustrating the state after the point group D2 and image D1b are processed in cooperation with each other. [Figure 9] FIG. 13 is a diagram showing an example of the configuration of point cloud-image linked data D4 after point cloud-image linkage. [Figure 10] 13 is a diagram showing the processing contents of the point cloud-CAD matching unit 23. [Figure 11] 4 is a diagram showing the processing contents of the point cloud-image-CAD linking unit 24. FIG. [Figure 12] FIG. 13 is a diagram showing an example of image display using point cloud-image-CAD linkage information D6. [Figure 13] FIG. 13 is a diagram showing an example of image display using point cloud-image-CAD linkage information D6. [Figure 14] FIG. 4 is a diagram showing the flow of point cloud-image linking processing in the point cloud-image linking unit 22. [Figure 15] FIG. 1 is a diagram showing a method for creating a point cloud image (point cloud before thinning). [Figure 16] FIG. 13 is a diagram showing the state in which point group D2 is arranged in a panoramic image. [Figure 17] FIG. 13 is a diagram showing the flow of point cloud-CAD linkage processing in the point cloud-CAD matching unit 23. [Figure 18] FIG. 2 is a diagram showing the flow of point cloud-image-CAD linking processing in the point cloud-image-CAD linking unit 24. [Figure 19] FIG. 12 is a diagram showing a flow of display processing in the display unit 12. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Hereinafter, embodiments of the present invention will be described with reference to the drawings. EXAMPLES

[0016] FIG. 1 is a diagram showing an example of the overall configuration of an inspection support device using an image information processing device according to an embodiment of the present invention.

[0017] In FIG. 1, an inspection support device 10 processes image information of a plant obtained from a laser scanner 11 in an image information processing device 20 and outputs the processed results to a display device 12, thereby presenting information for supporting the inspection of the plant.

[0018] The image information processing device 20, which is composed of a database and an arithmetic unit of a computer device, has as its databases a high-resolution image database DB1 that stores high-resolution image information D1, a low-density point cloud database DB2 that stores low-density point cloud information D2, a CAD model database DB3 that stores CAD model information D3, a point cloud-image linkage database DB4 that stores point cloud-image linkage information D4, a point cloud-CAD linkage database DB5 that stores point cloud-CAD linkage information D5, and a point cloud-image-CAD linkage database DB6 that stores point cloud-image-CAD linkage information D6.

[0019] Moreover, the processing contents in the calculation unit can be functionally expressed as follows: it has the processing functions of a point cloud thinning unit 21, a point cloud-image linking unit 22, a point cloud-CAD matching unit 23, and a point cloud-image-CAD linking unit 24.

[0020] Below, specific examples will be used to explain each function constituting the inspection support device 10 and the information handled by each unit. First, regarding the laser scanner 11, Fig. 2 shows an example of an environment measured by the laser scanner 11. In this example, the laser scanner 11 equipped with a camera is placed in a plant such as a nuclear power plant, and a laser 16 is irradiated onto equipment 14 and pipes 15a, 15b, which are objects to be monitored and installed on a floor 13 with a wall W in the background, to obtain image information D1 of the environment within the plant.

[0021] Here, the image information D1 is information including a high-density point cloud D1a obtained by measurement with the laser scanner 11 and photographic data (pixels) D1b obtained by the laser scanner measurement. Note that the photographic data (pixels) D1b may be simply referred to as an image.

[0022] Fig. 3 is a diagram showing an example of a high-density point cloud D1a obtained by measurement using the laser scanner 11. Fig. 4 is a diagram showing an example of the data configuration of the point cloud D1a. According to this diagram, the data of the point cloud D1a is composed of, for example, three-dimensional position information P of the X-axis, Y-axis, and Z-axis with the installation position of the laser scanner 11 as the reference position 0, and color information (RGB) of the laser irradiation points. The point cloud D1a is stored in a high-resolution image database DB1.

[0023] The point cloud thinning unit 21 in Fig. 1 performs thinning processing on the high-density point cloud D1a obtained by measurement with the laser scanner 11, and obtains a low-density point cloud D2 as shown in Fig. 5, for example. The idea of ​​thinning may be uniform thinning or thinning according to a predetermined rule. The predetermined rule may be, for example, increasing the amount of thinning when the distances from the laser scanner 11 between adjacent points are the same or when there is little change in hue. The low-density point cloud D2 after the thinning processing has the same data structure as that in Fig. 4, and is stored in the low-density point cloud database DB2.

[0024] FIG. 6 is a diagram showing an example of photo data (pixels) D1b obtained by laser scanner measurement. FIG. 6 is an example of an image showing equipment 14 and pipes 15a and 15b as monitored objects against a background of a wall W and a floor 13. FIG. 7 shows information on each pixel, for example, with the upper left corner of the image as the origin and coordinates (image coordinates) on the vertical axis Ix and the horizontal axis IY. The photo data D1b in FIG. 7 is composed of information on image coordinates (vertical axis Ix, horizontal axis IY) and color information (RGB) of the laser irradiation point. Each pixel has color information (RGB). The photo data D1b is stored in a high-resolution image database DB1.

[0025] Returning to Fig. 1, the point cloud-image linking unit 22 performs a process of linking the low-density point cloud D2 after the thinning process in Fig. 5 with the image D1b in Fig. 6. This involves adding the information of the low-density point cloud D2 to the information of the image D1b, and since the image D1b has information on image coordinates (vertical axis Ix, horizontal axis IY) with the upper left corner of the image as the origin, and the point cloud D2 after thinning has three-dimensional position information P of the X-axis, Y-axis, and Z-axis with the installation position of the laser scanner 11 as the reference position 0, and since there is a correlation between these two coordinates, they can be converted into each other's coordinates. This allows the two pieces of information to be merged.

[0026] Figure 8 shows an example of the state after the point cloud D2 and image D1b have been processed together, in which the thinned-out point cloud D2, indicated by "●", is placed on top of an image showing equipment 14 and pipes 15a and 15b against a background of walls W and floor 13.

[0027] 9 shows an example of the configuration of point cloud-image linkage data D4 after point cloud-image linkage. Point cloud-image linkage data D4 is composed of two coordinate systems (image coordinate system I with vertical axis Ix and horizontal axis IY, and three-dimensional coordinate system P with X-, Y-, and Z-axes) and color information C (RGB). However, pixels where a point cloud exists have RGB and XYZ values. Pixels where a point cloud does not exist have only RGB. Point cloud-image linkage data D4 after point cloud-image linkage is stored in point cloud-image linkage database DB4.

[0028] Returning to FIG. 1, the point cloud-CAD collation unit 23 collates information D3 of the monitored object held in the CAD model database DB3 with low-density point cloud information D2 stored in the low-density point cloud database DB2.

[0029] 10 is a diagram showing the processing contents of the point cloud-CAD matching unit 23. First, in the upper left corner, CAD models of the equipment 14 and pipes 15a, 15b, which are the objects to be monitored, are shown, and the CAD model database DB3 holds information D3 on their dimensions, configuration, materials and various attributes. In addition, in the upper right corner, a low-density point cloud D4 of the equipment 14 and pipes 15a, 15b, which are also the objects to be monitored, is shown, and the low-density point cloud database DB2 holds information on the three-dimensional coordinate position P of the point cloud and color information C as shown in FIG.

[0030] The point cloud-CAD matching unit 23 uses the position information contained in the CAD model information D3 and the point cloud D4 to match and merge the CAD model information D3 and the point cloud information D4. This process does not merely link and organize information, but also obtains values ​​that are the information differences between the two pieces of information about the equipment 14 and the pipes 15a and 15b that are the objects to be monitored. These are information differences that indicate the differences in size of the equipment 14 and the pipes 15a and 15b, and the deviations in the installation positions. An example of point cloud-CAD linkage information D5 obtained by this naming process is shown at the bottom of FIG. 10, and this information is held in the point cloud-CAD linkage database DB5.

[0031] The processing of the point cloud-image-CAD linking unit 24 will be described with reference to Fig. 11. The left side of Fig. 11 shows an example of point cloud-image linking information D4 (Fig. 9) stored in point cloud-image linking database DB4, and the right side shows an example of point cloud-CAD linking information D5 (Fig. 10) stored in point cloud-CAD linking database DB5. Both of these pieces of information D4 and D5 contain three-dimensional position information P of the X-axis, Y-axis, and Z-axis, so this can be used as key information to merge these data and create point cloud-image-CAD linking information D6 shown in the lower part of Fig. 11.

[0032] 12 and 13 show examples of images displayed on the display unit 12 using the finally created point cloud-image-CAD link information D6. According to the image display example of FIG. 12, the point clouds of pipes, equipment, and other wall and floor parts are displayed in different colors according to their respective parts, based on the CAD model IDs assigned to each point. Each point is also assigned the ID of the closest CAD model. Also, the CAD model ID stored in the clicked pixel (or the pixel closest to it) can be displayed.

[0033] In the display example in Figure 13, the points are color-coded according to the difference in position and size between the CAD model and the point cloud. The area indicated by R1 has a large difference, the area indicated by R2 has a medium difference, and the area indicated by R3 has a small difference, which can be easily recognized.

[0034] 14 is a diagram showing the flow of point cloud-image linking processing in the point cloud-image linking unit 22. In this processing, first, in processing step S21, (x, y, z, r, p, g) are read from a high-resolution image database DB1 that stores high-resolution image information D1 as information D1b of a high-density point cloud measured by the laser scanner 11.

[0035] In process step S22, scan information is obtained, which includes the origin coordinates of the laser scanner, the laser irradiation range (maximum / minimum angles in the φ and θ directions), and the laser irradiation interval (laser irradiation interval in the φ and θ directions, or the number of laser irradiations).

[0036] FIG. 15 is a diagram showing a method for creating a point cloud image (point cloud before thinning), and the laser irradiation range and irradiation interval of the laser scanner 11 will be described with reference to this diagram.

[0037] The concept of laser scanning is shown on the left side of Figure 15. In the measurement by the laser scanner 11, first, the laser is irradiated at regular intervals in the θ direction from 0° to approximately 180°. Next, the scanner driving unit is rotated at regular intervals in the φ direction, and the laser is again irradiated at regular intervals in the φ direction. This is repeated until the angle reaches 0° to approximately 360° in the φ direction, and a point cloud of 360° is obtained.

[0038] The right side of Figure 15 shows a grid-like point cloud, and the point cloud data measured by the laser scanner 11 can be saved as an aligned point cloud (file format called PTX or e57) in which the points are aligned in the order of laser irradiation by the scanner's attached software. The aligned point cloud contains the following information: the laser irradiation order of the point cloud measured by the laser scanner, the laser irradiation range (maximum / minimum angles in the φ and θ directions), and the laser irradiation interval (laser irradiation interval in the φ and θ directions, or the number of laser irradiations). If the aligned point cloud is aligned in a grid-like manner based on this information as shown on the right side of Figure 15, a panoramic point cloud image can be created (each pixel stores a point x, y, z, r, g, b). Here, φ and θ are angles, and Ix and Iy are pixel numbers, and angles and pixel numbers can be converted into each other. In addition, points are stored in all pixels.

[0039] In processing step S23, a thinning process is performed on the high-density point group D1a obtained by measurement with the laser scanner 11, to obtain a low-density point group D2 as shown in Fig. 5. A known thinning method can be applied, and it may be either thinning at equal intervals (constant distance intervals) or random thinning.

[0040] In processing step S24, the point cloud D2 is arranged in a panoramic image using the scan information acquired in processing step S22. Fig. 16 shows the state in which the point cloud D2 is arranged in a panoramic image. The point cloud is arranged on the pixels in Fig. 15. A method for creating a point cloud image (point cloud after thinning) will be described with reference to Fig. 16. At this time, the thinned out point cloud is not aligned (not arranged in the order of laser irradiation), and therefore cannot be easily arranged in a lattice as it is, so for example, the following processing is performed.

[0041] First, φ and θ of each point are calculated based on the positional relationship between the scanner origin coordinate 0 and each point coordinate. This can be calculated mathematically using a known method. Next, the image coordinates of each point are calculated using φ and θ of each point, the laser irradiation range (φmax, φmin, θmax, θmin) and the irradiation interval (Δφ, Δθ) acquired in advance. For example, Ix=(φ-φmin)÷(φmax-φmin)×φmax-φmin)÷Δφ for the pixel number in the φ direction, and Iy=(θ-θmin)÷(θmax-θmin)×(θmax-θmin)÷Δθ for the pixel number in the θ direction.

[0042] In processing step S25, a panoramic image taken by a camera mounted on the laser scanner 11 is read. This is the information shown in FIG.

[0043] In processing step S25, if the angle of view of the panoramic image exceeds 360° and there is an overlapping portion, the overlapping portion is removed. This processing can be performed using a known image processing technique.

[0044] In processing step S26, the pixels of the camera image and the point cloud image are overlapped, and point cloud data (X, Y, Z) is assigned to each pixel of the camera image. Through this series of processing, point cloud-image linkage information D4 is generated and stored in the point cloud-image linkage database DB4.

[0045] Fig. 17 is a diagram showing the flow of point cloud-CAD linkage processing in the point cloud-CAD matching unit 23. In this processing, first, in processing step S31, the point cloud D2 thinned out in processing step S3 of the point cloud-image linkage processing in Fig. 14 is acquired, and in processing step S32, a CAD model D3 is acquired.

[0046] In process step S33, the point cloud D2 and the CAD model D3 are aligned, and in process step S34, the point cloud and the CAD model are linked to calculate the differences in the positions and sizes of the equipment 14 and the pipes 15a and 15b. In process step S35, the ID of the closest CAD model and the difference (distance) are assigned to each point. Through this series of processes, point cloud-CAD linkage information D5 is generated and stored in the point cloud-CAD linkage database DB5.

[0047] 18 is a diagram showing the flow of point cloud-image-CAD linking processing in point cloud-image-CAD linking unit 24. In this processing, first in processing step S41, point cloud-image linking information D4 is obtained from point cloud-image linking database DB4, and in processing step S42, point cloud-CAD linking information D5 is obtained from point cloud-CAD linking database DB5, and data is combined when the three-dimensional coordinates X, Y, and Z of the point clouds match. Through this series of processing, point cloud-image-CAD linking information D6 is generated and stored in point cloud-image-CAD linking database DB6.

[0048] 19 is a diagram showing a flow of display processing in the display unit 12. In this processing, first, in processing step S51, point cloud-image-CAD linkage information D6 is acquired from the point cloud-image-CAD linkage database DB6. In processing step S52, the image is displayed, and it is possible to display each point in a different color using the CAD model ID or the difference.

[0049] In processing step S53, the coordinates (Ix, Iy) of the pixel clicked by the user via an input unit such as a mouse (not shown in FIG. 1) are obtained.

[0050] According to the embodiment of the present invention described above, a high-resolution and lightweight point cloud image D4 can be generated by linking a high-resolution image D1a measured by the laser scanner 11 with a thinned-out low-density point cloud D2. Also, by comparing the point cloud D2 with the CAD model D3 and detecting the difference between them, it is possible to compare the difference between the design and construction regardless of the facility shape.

[0051] This is achieved by linking the point cloud D2 and image D1a measured by the laser scanner with the design CAD model D3, and it is possible to inspect all facilities that can be measured by the laser scanner 11 in the VR space. This means that even in the case of plant facilities that are subject to restrictions and where it is difficult for workers to enter, such as nuclear facilities, it is possible to inspect the power plant facilities without going to the site, even without requiring entry, and the number of inspection days can be reduced from two weeks to around one day.

[0052] This invention makes it possible to display high-resolution point cloud images including CAD differences in a practical amount of time; for example, the processing time can be reduced from 100 seconds to 5 seconds, and information that can only be obtained by comparing the point cloud with CAD (differences between the point cloud and CAD, attributes such as facility names) can be displayed on the image. [Explanation of symbols]

[0053] 10: Inspection support device 11: Laser scanner 12:Display device 20: Image information processing device 21: Point cloud thinning unit 21 22: Point cloud-image linking section 23: Point cloud-CAD matching section 24: Point cloud-image-CAD linking section D1: High-resolution image information DB1: High-resolution image database D2: Low density point cloud information DB2: A low density point cloud database D3:CAD model information DB3: CAD model database D4: Point cloud-image linkage information DB4: Point cloud-image link database D5: Point cloud - CAD linkage information DB5: Point cloud-CAD linked database D6: Point cloud - image - CAD linkage information DB6: Point cloud-image-CAD linked database

Claims

1. An image information processing device that inputs images and high-density point clouds from a camera and a laser scanner aimed at on-site equipment and processes the information in a calculation unit of a computer device, The calculation unit has a function of a point cloud thinning unit that thins out the high-density point cloud to obtain a low-density point cloud, and a point cloud-image linking unit that obtains point cloud-image linking information in which information of the low-density point cloud is linked and arranged on the image, and The image, which is composed of multiple pixels, includes position information and color information of the pixels on the image, and the point cloud includes position information and color information between the device and the laser scanner, and an image information processing device is characterized in that the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud.

2. 2. The image information processing apparatus according to claim 1, The calculation unit has a function of a point cloud-CAD matching unit that matches a CAD model including structure and attribute information of the on-site equipment with the low-density point cloud to obtain point cloud-CAD linkage information, An image information processing device characterized by obtaining the point cloud-CAD linkage information by matching the CAD model with the low-density point cloud using position information contained in the structure of the equipment held by the CAD model and position information of the point cloud.

3. 3. The image information processing apparatus according to claim 2, The image information processing apparatus is characterized in that the calculation unit has the function of a point cloud-image-CAD linking unit that links the point cloud-image linking information and the point cloud-CAD linking information to obtain point cloud-image-CAD linking information.

4. 4. The image information processing apparatus according to claim 2, The image information processing apparatus, wherein the point cloud-CAD linkage information includes a difference between position information included in the structure of the device held by the CAD model and position information of the point cloud.

5. An inspection support device including a camera and a laser scanner aimed at an on-site device, an input unit that inputs an image and a high-density point cloud from the camera and the laser scanner, a calculation unit that processes information from the input unit, and a display unit that displays a processing result of the calculation unit, The calculation unit has a function of a point cloud thinning unit that thins out the high-density point cloud to obtain a low-density point cloud, and a point cloud-image linking unit that obtains point cloud-image linking information in which information of the low-density point cloud is linked and arranged on the image, and displays the point cloud-image linking information on the display unit, The image, which is composed of multiple pixels, includes position information and color information of the pixels on the image, and the point cloud includes position information and color information between the equipment and the laser scanner, and an inspection support device characterized in that the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud.

6. The inspection support device according to claim 5, The calculation unit has a function of a point cloud-CAD matching unit that matches a CAD model including structure and attribute information of the on-site equipment with the low-density point cloud to obtain point cloud-CAD linkage information, displays the point cloud-CAD linkage information on the display unit, and An inspection support device characterized by obtaining the point cloud-CAD linkage information by matching the CAD model with the low-density point cloud using position information contained in the structure of the equipment held by the CAD model and position information of the point cloud.

7. The inspection support device according to claim 6, The calculation unit is provided with a function of a point cloud-image-CAD linkage unit that links the point cloud-image linkage information and the point cloud-CAD linkage information to obtain point cloud-image-CAD linkage information, and is characterized in that the point cloud-image-CAD linkage information is displayed on the display unit.

8. The inspection support device according to claim 6 or 7, An inspection support device characterized in that the point cloud-CAD linkage information includes a difference between position information contained in the structure of the equipment held by the CAD model and position information of the point cloud.

9. An image information processing method for inputting an image and a high-density point cloud from a camera and a laser scanner aimed at an on-site device, and processing the information in a calculation unit of a computer device, comprising: The calculation unit thins out the high-density point cloud to obtain a low-density point cloud, and obtains point cloud-image link information in which information of the low-density point cloud is linked and arranged on the image, and An image information processing method characterized in that the image, which is composed of multiple pixels, includes position information and color information of the pixels on the image, and the point cloud includes position information and color information between the device and the laser scanner, and the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud.

10. An inspection support method for obtaining images and high-density point cloud information from a camera and a laser scanner aimed at an on-site device, processing the information, and displaying the processing results, comprising: The high-density point cloud is thinned out to obtain a low-density point cloud, and point cloud-image link information is obtained by linking and arranging information of the low-density point cloud on the image, and the point cloud-image link information is displayed. The inspection support method is characterized in that the image, which is composed of multiple pixels, includes position information and color information of the pixels on the image, and the point cloud includes position information and color information between the equipment and the laser scanner, and the low-density point cloud information is linked on the image using the position information of the image and the position information of the point cloud.

Images