JP5745438B2 - Inspection method and inspection apparatus - Google Patents

Description

  The present invention relates to an inspection method and an inspection apparatus for acquiring and inspecting an image by a camera, and in particular, a resolution corresponding to a structure or a defective portion of an image acquired by a camera so that a defect can be determined during the inspection. The present invention relates to a technique for improving image quality such as improvement.

  Nuclear power plants and the like are required to have a high level of safety and must be thoroughly inspected regularly. As the inspection object, for example, a reactor pressure vessel, a structure such as a shroud, a core support plate, and a fuel assembly in the vessel are inspected. There are also non-reactor inspections such as inspection of fuel assemblies stored outside the reactor.

  As one of inspection methods, there is a method of visually inspecting a moving image obtained by imaging the surface of an inspection object using a camera. In this visual inspection, the camera is photographed close to the object. Get color or grayscale video from the camera. The acquired video is displayed on the display, and the inspector visually inspects it.

  Moreover, the acquired moving image is recorded so that it can be confirmed later. In addition, the camera is equipped with a drive device and can be operated remotely so as to move the imaging location, or a mechanism that allows the inspector to manually operate the camera from a remote location.

  The examination may be performed in an environment where there is a lot of radiation such as gamma rays. In this case, radiation noise is superimposed on the image. Also, due to radiation, the electronic circuitry in the camera is damaged and its function is gradually lost.

  Accordingly, the inspection moving image has poor visibility, and there is a problem that it is difficult to obtain high reliability in the inspection of the inspection object.

  This problem is addressed by a method of devising the camera and a method of devising processing of the acquired moving image. The former is a method in which, for example, a camera is provided with a radiation shield so that radiation does not hit the camera. The latter is a method of performing image quality improvement processing such as noise removal processing on the acquired moving image, for example.

  On the other hand, in recent years, it has been required to increase the resolution of an inspection moving image so that a smaller defect can be detected so that a hard-to-see defect can be found.

  As a countermeasure for this, there is a method of increasing the resolution by image processing. As an example, there is a method of performing super-resolution processing on the acquired moving image.

  For example, there is a technique described in Japanese Patent Application Laid-Open No. 2008-278143 (Patent Document 1). This publication describes that “a high-resolution image having a resolution higher than that of the inspection image is created from the inspection image”. With this configuration, the inspection image is subjected to super-resolution processing to improve the resolution. Yes.

JP 2008-278143 A

  In the method described in Patent Document 1, super-resolution processing is uniformly performed on a target image. However, the image quality of inspection videos of nuclear power plants, etc. may vary depending on the image frame in the video and the position on each image frame. As a result of uniform image processing, the entire image quality of the inspection video is optimal. It is difficult to make.

  For example, in an inspection of a nuclear power plant or the like, an inspection object is imaged while moving a camera. For this reason, the distance between the camera and the inspection object changes for each image frame in the moving image. In addition, since the inspection object has a structure having a depth, the distance between the camera and the inspection object varies depending on the position on each image frame.

  As a result, the degree of blurring of the image changes for each image frame or for each position on each image frame. When uniform image processing is performed on this moving image, the image quality may be insufficient when viewed for each image frame or for each position on each image frame.

  SUMMARY OF THE INVENTION An object of the present invention is to provide an inspection method and an inspection apparatus capable of improving image quality such as resolution improvement corresponding to a structure or a defective portion of an image acquired by a camera.

  The above and other objects and novel features of the present invention will be apparent from the description of this specification and the accompanying drawings.

  Of the inventions disclosed in the present application, the outline of typical ones will be briefly described as follows.

  In other words, the outline of a typical one is that an image processing apparatus acquires a moving image of an inspection object imaged by a camera, divides the acquired moving image into a plurality of image frames, and divides each image frame into a plurality of divided regions. Divide and create a divided video, calculate the index value related to the strength of the image quality improvement processing for each divided video, set the strength of the image quality improvement processing according to the index value value for each divided video, and perform the image quality improvement processing To create a high-quality moving image, display the created high-quality moving image on a display device, and store the high-quality moving image in a storage device.

  Further, the camera has a larger number of pixels than the number of screen display pixels to be displayed on the display device or the storage pixel to be stored in the storage device, and the image processing device acquires a moving image of the inspection object imaged by the camera, The obtained video is divided into a plurality of image frames, each image frame is divided into a plurality of divided areas to create a divided video, and the signal component is saved after reduction using the reduction ratio used in the reduction process. The image quality improvement process is set, the image quality improvement process set for each divided video is applied to create a high-quality video, and the reduction process set for each divided video is applied from the high-quality video to the high-quality reduced video. The created high-quality reduced video is displayed on the display device, and the high-quality video is stored in the storage device.

  The effects obtained by typical ones of the inventions disclosed in the present application will be briefly described as follows.

  In other words, the effect obtained by a typical one is that it is possible to improve the image quality such as improving the resolution corresponding to the structure or defect part of the image acquired by the camera, and display a moving image with good visibility. Can be saved.

It is a block diagram which shows the structure of the inspection apparatus which concerns on Embodiment 1 of this invention. It is a block diagram which shows the structure of the image processing apparatus of the inspection apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows the sequence of the visual inspection by the inspection apparatus which concerns on Embodiment 1 of this invention. It is explanatory drawing for demonstrating the setting of the intensity | strength of index value calculation and image quality improvement processing of the inspection apparatus which concerns on Embodiment 1 of this invention. It is explanatory drawing for demonstrating the division | segmentation into the division area of the division | segmentation moving image preparation of the inspection apparatus which concerns on Embodiment 2 of this invention. (A), (b) is explanatory drawing for demonstrating the setting of the intensity | strength of index value calculation and image quality improvement processing of the inspection apparatus which concerns on Embodiment 3 of this invention. It is explanatory drawing for demonstrating the division | segmentation method to the division | segmentation moving image of the inspection apparatus which concerns on Embodiment 4 of this invention. It is explanatory drawing for demonstrating the setting of the intensity | strength of index value calculation and image quality improvement processing of the inspection apparatus which concerns on Embodiment 5 of this invention. (A), (b) is explanatory drawing for demonstrating the example of a screen display by GUI of the inspection apparatus which concerns on Embodiment 6 of this invention. It is explanatory drawing for demonstrating estimation of the radioactive damage degree of the inspection apparatus which concerns on Embodiment 7 of this invention. (A), (b) is explanatory drawing for demonstrating the example of a screen display by GUI of the inspection apparatus which concerns on Embodiment 7 of this invention. It is explanatory drawing for demonstrating the setting of the intensity | strength of index value calculation and image quality improvement processing of the inspection apparatus which concerns on Embodiment 8 of this invention. (A), (b) is explanatory drawing for demonstrating the example of a screen display by GUI of the inspection apparatus which concerns on Embodiment 8 of this invention. It is explanatory drawing for demonstrating the division | segmentation into the division area of the division | segmentation moving image preparation of the inspection apparatus which concerns on Embodiment 9 of this invention. It is explanatory drawing for demonstrating the example of an imaging of the test target object of the inspection apparatus which concerns on Embodiment 10 of this invention. (A)-(c) is explanatory drawing for demonstrating the example of a screen display by GUI of the inspection apparatus which concerns on Embodiment 11 of this invention. It is explanatory drawing for demonstrating an example of the trimming of the inspection apparatus which concerns on Embodiment 12 of this invention. It is explanatory drawing for demonstrating an example of the trimming of the inspection apparatus which concerns on Embodiment 12 of this invention. (A), (b) is explanatory drawing for demonstrating an example of the trimming of the inspection apparatus which concerns on Embodiment 12 of this invention.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment, and the repetitive description thereof will be omitted.

(Embodiment 1)
<Configuration of inspection device>
The configuration of the inspection apparatus according to Embodiment 1 of the present invention will be described with reference to FIG. FIG. 1 is a configuration diagram showing a configuration of an inspection apparatus according to Embodiment 1 of the present invention.

  In FIG. 1, the inspection apparatus includes, for example, a camera 201, an image processing apparatus 202, a storage apparatus 203, and a GUI 204 that is a display apparatus. When the inspection object 205 is a nuclear reactor in which the influence of radiation is large, the inspection is performed by placing only the camera 201 near the inspection object 205, and the image processing device 202, the storage device 203, and the GUI 204 other than the camera 201 Go outside the environment where there are many.

  The camera 201 may include an illumination 206 and a drive unit (not shown). The illumination 206 illuminates the inspection object 205. The inspection object 205 is imaged with the camera 201 to obtain a moving image. The camera 201 can capture a color moving image or a gray scale moving image. As the type of the camera 201, an imaging tube, a CCD, a CMOS, or the like can be used.

  A moving image from the camera 201 is transmitted to the image processing apparatus 202 through the cable 207. Communication between the camera 201 and the image processing apparatus 202 may be performed wirelessly.

<Configuration of image processing apparatus>
Next, the configuration of the image processing apparatus of the inspection apparatus according to Embodiment 1 of the present invention will be described with reference to FIG. FIG. 2 is a block diagram showing the configuration of the image processing apparatus of the inspection apparatus according to Embodiment 1 of the present invention.

  In FIG. 2, the image processing apparatus 202 includes an image input unit 2021 that inputs a moving image captured by the camera 201, an image memory 2022 that temporarily stores the input moving image, and a divided moving image that uses the moving image stored in the image memory 2022. A divided video setting unit 2023 for setting the index, an index value calculation unit 2026 for calculating an index value for each divided video set by the divided video setting unit 2023, and an index value calculated by the index value calculation unit 2026 An image quality improvement divided moving image setting unit 2027 for setting a divided moving image, an image quality improvement setting unit 2028 for setting an image quality improvement strength for each divided moving image for image quality improvement set by the image quality improving divided moving image setting unit 2027, and an image quality improving divided moving image setting unit 2027 Set by the image reduction setting unit 2029 and the image quality improvement setting unit 2028 for setting the image reduction for each divided moving image for image quality improvement set in. The image quality improvement image reduction for performing the image quality improvement and the image reduction of the divided video for the image quality improvement set by the image quality improvement divided moving image setting unit 2027 using the image quality improvement strength and the image reduction setting set by the image reduction setting unit 2029 A unit 2024 and an image output unit 2025 for outputting a moving image with improved image quality and image reduction are provided.

  Here, a configuration without the image quality improvement divided moving image setting unit 2027 and the image reduction setting unit 2029 is also conceivable when not dividing or not reducing. It is also conceivable that only the image quality improvement is performed by the image quality improvement image reduction unit 2024.

  The image processing apparatus 202 outputs an image with improved image quality and reduced image or an input image from the image output unit 2025, displays it on the GUI 204, records it in the storage device 203, and saves it.

<Visual inspection sequence>
Next, a visual inspection sequence by the inspection apparatus according to the first embodiment of the present invention will be described with reference to FIG. FIG. 3 is a diagram showing a sequence of visual inspection by the inspection apparatus according to Embodiment 1 of the present invention.

  The inspection procedure 101 includes a camera imaging step S102, a divided moving image creating step S103, an index value calculating step S104, an image quality improving divided moving image creating step S107, an image quality improvement setting step S108, an image reduction setting step S109, an image quality improving image reducing step S105, It consists of a screen display step S106.

  Here, a sequence without the image quality improvement divided moving image creating step S107 and the image reduction setting step S109 is also conceivable. Since the video of the camera is a moving image, the above steps are repeated for each frame in principle.

  In the camera imaging step S102, the moving image 106 obtained by imaging the inspection object 205 by the camera 201 is acquired. In a divided moving image creating step S103, a divided moving image 112 is created for the acquired moving image 106.

  In an index value calculation step S104, an index value 113 related to the strength of image quality improvement processing is calculated for each divided moving image. In a divided moving image creating step S107 for improving image quality, a divided moving image 114 is created based on the index value. In the example illustrated in FIG. 3, for example, the B area 117 in which the structure 115 and the defect 116 are reflected and the C area 118 that is the background are respectively divided moving images.

  Further, the A area 119 obtained by trimming a part of the acquired moving image 106 may be a divided moving image. In the image quality improvement setting step S108, the image quality improvement strength is set for each divided moving image. In the image reduction setting step S109, image reduction is set for each divided moving image. In the image quality improvement image reduction step S105, the divided moving image is subjected to image quality improvement processing using the image quality improvement strength and image reduction using the image reduction setting to create a high quality video 111.

  It is also conceivable that the high-quality moving image 111 is created only by improving the image quality. In the example illustrated in FIG. 3, for example, the B moving image 120 that is a divided moving image of the B region is subjected to image quality improvement processing to create a high resolution high quality moving image 121, and the high resolution high quality moving image 121 is reduced to divide the C region. A reduced high-resolution high-quality moving image 123 is created together with the reduced C moving image 122 obtained by reducing the moving image.

  Alternatively, the zoom high-quality moving image 125 may be created by performing the image quality improvement process on the trimming A moving image 124 that is the divided moving image of the A area 119. The image quality improving image reduction step S105 is representative, and other combinations may be used.

  In the screen display step S106, the high-quality moving image 111 is displayed on the GUI 204 for visual inspection. Alternatively, the high-quality moving image 111 is stored in the storage device 203.

<Image processing>
Next, image processing by the inspection apparatus according to Embodiment 1 of the present invention will be described.

  In the present embodiment, the inspection object is imaged with a camera in an environment affected by radiation to acquire a moving image of the inspection object, the acquired moving image is divided into a plurality of image frames, and each of the image frames is divided into a plurality of divisions. Divide into regions to create divided videos, calculate index values related to the strength of image quality improvement processing for each divided video, set the strength of image quality improvement processing using the index values for each divided video, and improve image quality To create a high-quality video and display the high-quality video on the screen, or store the high-quality video in the storage device.

  When uniform image quality improvement processing is performed on an acquired moving image as in the prior art, there is a problem that the image quality becomes insufficient when viewed for each image frame or for each divided region obtained by dividing each image frame into a plurality of regions. In the acquired moving image, the image quality improvement processing should be strongly performed at a portion where the effect of the image quality improvement processing appears, and the image quality improvement processing should be weakly performed at a portion where the side effect of the image quality improvement processing occurs.

  Therefore, in the present embodiment, the acquired moving image is divided into a plurality of image frames, and the image frame is further divided into a plurality of divided areas to create a divided moving image, and different image quality improvement processing is performed for each divided moving image.

  As a result, it is possible to improve the overall visibility by improving the quality of the moving image only for the divided moving image that has the effect of the image quality improvement processing in the acquired moving image.

  Further, in the related art, there is a problem that the strength of image quality improvement processing cannot be set appropriately when image quality improvement processing is performed for each divided moving image. It is necessary to provide a standard for setting the strength of the image quality improvement processing.

  Therefore, in this embodiment, an index value related to the strength of the image quality improvement processing is calculated for each divided moving image as a guideline for setting the strength of the image quality improvement processing. Thereby, when performing the image quality improvement processing for each divided moving image, it is possible to obtain a guideline for appropriately setting the strength of the image quality improvement processing.

  Further, in the related art, since the strength of the image quality improvement process changes discontinuously at the boundary between the divided areas, there is a problem that the image changes unnaturally at the boundary between the divided areas. It is necessary to prevent the image from changing unnaturally at the boundary between the divided areas.

  Therefore, in the present embodiment, the intensity is adjusted and set so as to continuously change. Thereby, it can suppress that an image changes unnaturally in the boundary of a division area.

  Specifically, in this embodiment, image restoration processing is used for image quality improvement processing.

  Image restoration processing is a generally known technique. For example, a degradation process is defined by a model in which a blurred image is generated by convolution of the original image, and the blurred function is deconvolved in the degraded image. This is a technique for restoring the original image. In general, the blur function is often expressed by a two-dimensional Gaussian function.

  If the image restoration processing is simply applied to the inspection object of the present embodiment, the structure or the defect is sharpened, but there is a problem that noise is emphasized. If there is no structure or defect, there is no target to be restored and noise is only emphasized, so image restoration processing should be weakly applied.

  Therefore, in this embodiment, when there is a structure or a defect, image restoration is strongly performed and sharpened, and when there is only noise, image restoration is weakened and noise enhancement is suppressed to improve overall visibility. It becomes possible.

<Indicator value calculation and image quality improvement processing intensity setting>
Next, referring to FIG. 4, index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the first embodiment of the present invention will be described. FIG. 4 is an explanatory diagram for explaining index value calculation and intensity setting of image quality improvement processing of the inspection apparatus according to the first embodiment of the present invention.

  In the example shown in FIG. 4, for example, a structure 302 is shown in an image frame 301 with the acquired moving image 106, and a defect 303 exists on the structure 302 on a line.

  As a moving image dividing method, for example, the acquired moving image is divided into a plurality of image frames, and each image frame is divided into a plurality of divided regions, and the divided moving image 304 is created. An arbitrary shape is possible for the division into the divided areas, but FIG. 3 shows an example in which the divided areas are divided into strip-shaped divided areas. The boundary 310 of the divided area is indicated by vertical and horizontal dotted lines in the figure. One section surrounded by a dotted line is one divided moving image.

  The index value calculation is actually performed using all the pixel values of the divided moving image. However, in order to simplify the description, only the AA ′ section of the image frame 301 will be described below. The pixel value of the AA ′ cross section of the image frame 301 is as shown in a pixel value graph 305, for example. One memory on the horizontal axis of the pixel value graph 305 corresponds to one divided moving image. It is assumed that the number of pixels in the AA ′ cross section is much larger than the number of divided moving images in the AA ′ cross section, and one memory on the horizontal axis includes a plurality of pixels.

  For example, the index value is defined as the degree of existence of a structure or a defect, and the index value is calculated, for example, by subjecting the divided moving image to a smoothing process, subtracting it from the original divided moving image, and subtracting it.

  When calculation is performed for each divided moving image of the AA ′ cross section, the calculation result is as shown in an index value graph 306, for example. One memory on the horizontal axis of the index value graph 306 corresponds to one divided moving image. In order to calculate one index value for each divided moving image, one index value is plotted for each memory on the horizontal axis of the index value graph 306.

  The image quality improvement processing is, for example, image restoration processing, for example, processing for deconvolution of the blur function. The strength of the image quality improvement processing is the magnitude of the blur function. The larger the blur function, the stronger the image restoration. Since the image restoration process has a property of sharpening the structure or the defect, the image restoration process is performed by setting the blur function to be larger as the degree of existence of the structure or the defect is larger. The relationship between the index value and the intensity of image restoration is as shown by an index value-intensity graph 311.

  The intensity of the image restoration process set based on the calculated index value is, for example, an image restoration process intensity graph 307. One memory on the horizontal axis of the image restoration processing intensity graph 307 corresponds to one divided moving image. In order to set one image restoration processing strength for one divided moving image, one strength is plotted for one memory on the horizontal axis of the image restoration processing strength graph 307.

  Also, for example, in the vicinity of the boundary of the divided area, the intensity of the image restoration process on both sides of the boundary is interpolated, and the intensity of the image restoration process is continuously set at the boundary of the divided area by setting the intensity between both the intensity To change.

  For example, the intensity 312 of the third divided area and the intensity 313 of the fourth divided area are greatly different and discontinuous across the boundary 308 of the divided areas. Therefore, the intensity of the image restoration process on both sides of the boundary is further interpolated and changed smoothly, thereby continuously changing the intensity of the image restoration process at the boundary of the divided areas. The intensity of the interpolated image restoration process is, for example, an image restoration process intensity graph 309.

  One memory on the horizontal axis of the image restoration processing intensity graph 309 corresponds to one divided moving image. The intensity between the divided video and the divided video is a smooth change. Thereby, it can suppress that an image changes unnaturally in the boundary of a division area.

  With this method, it is possible to appropriately perform image quality improvement processing using the degree of existence of structures or defects.

(Embodiment 2)
In the second embodiment, the division into divided regions for each image frame is a grid-like division in the first embodiment, and the configuration of the inspection apparatus, the image processing in the image processing apparatus, and the like are described in the first embodiment. Same as 1.

<Division into divided areas for creating a divided video>
With reference to FIG. 5, the division into divided areas for creating a divided moving image by the inspection apparatus according to Embodiment 2 of the present invention will be described. FIG. 5 is an explanatory diagram for explaining division into divided areas for creating a divided moving image by the inspection apparatus according to the second embodiment of the present invention.

  As shown in FIG. 5, in the present embodiment, in the division into divided areas, the divided moving image 401 is created by dividing the image frame 301 into a plurality of grid-like divided areas. The boundary 402 of the divided area is indicated by vertical and horizontal dotted lines in the figure. One section surrounded by a dotted line is one divided moving image.

  In the first embodiment, an index value is calculated for each divided area, and different image quality improvement processing is performed for each divided area based on the index value. However, in order to obtain an appropriate image quality improvement result, what kind of area division is used? It is difficult to know whether it is desirable to calculate the index value in units before calculating the index value.

  Therefore, it is considered effective to give a unit for calculating the index value as a simple lattice shape, calculate the index value, and then determine a divided area for image quality improvement processing according to the index value. For such processing, in the second embodiment, index value calculation units are given in a grid pattern. As a result, it is possible to perform division into divided areas necessary for calculating the index value.

(Embodiment 3)
Embodiment 3 is the same as Embodiments 1 and 2, except that the index value is the degree of existence of a structure or defect in the divided video, the noise level of the divided video, or the blur level of the divided video. The configuration and the image processing in the image processing apparatus are the same as those in the first embodiment.

  In order to perform image quality improvement processing for each divided moving image, it is necessary to calculate an index value related to the strength of the image quality improvement processing for each divided moving image. For this purpose, an index value related to the strength of image quality improvement processing must be determined. Basically, it is necessary to perform an image quality improvement process on a portion where the image quality is degraded.

  The main cause of image quality degradation is noise or blur. On the other hand, there is a case where it is not necessary to perform image quality improvement processing on a portion where there is nothing that the user wants to see. What the user wants to see is a structure or a defect.

  Therefore, in this embodiment, the noise level, the blur level, and the existence level of structures or defects are used as index values. Accordingly, it is possible to set the strength of the image quality improvement processing for each divided moving image according to the index value related to the strength of the image quality improvement processing.

  For example, when image restoration processing is considered as image quality improvement processing, the image restoration processing sharpens a structure or a defect, but has a property of enhancing noise on the other hand. Therefore, image restoration processing should be performed only when there is a structure or a defect, for example. For example, when the noise is strong, the image restoration process should be suppressed. For example, when the blur of a moving image is strong, the image restoration process should be strong.

  Therefore, in the present embodiment, the index value is set as the degree of existence of a structure or a defect, and for example, the divided moving image is subjected to smoothing processing, subtracted from the original divided moving image, and calculated as an average of the subtraction results.

<Indicator value calculation and image quality improvement processing intensity setting>
Next, referring to FIG. 6, description will be given of index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the third embodiment of the present invention. FIG. 6 is an explanatory diagram for explaining index value calculation and intensity setting of image quality improvement processing of the inspection apparatus according to the third embodiment of the present invention. FIG. 6 (a) and FIG. 6 (b) are different. A video frame is shown.

  In FIG. 6A, a structure 302 is shown in an image frame 301 with the acquired moving image 106 as in the example shown in FIG. 4, and a defect 303 exists on the structure 302 on a line. It is assumed that noise due to radiation is superimposed on the image frame 301. The division into the divided areas is an example in which the division is performed in a lattice shape as in the second embodiment.

  Similarly to the first embodiment, only the AA ′ section of the image frame 301 will be described. The pixel value of the AA ′ cross section of the image frame 301 is as shown in a pixel value graph 305, for example.

  For example, the index value is set as the noise level, and for example, the divided moving image is smoothed, and is subtracted from the original divided moving image, and is calculated as the standard deviation of the subtraction result. When calculation is performed for each divided moving image of the AA ′ section, the calculation result is as shown in an index value graph 501, for example.

  In addition, as a method for determining the noise of the noise degree, for example, the determination is made based on the high frequency component of the frequency.

  As in the first embodiment, assuming that the image quality improvement processing is image restoration processing and the strength of the image restoration processing is the magnitude of the blur function, the image restoration processing is set to be suppressed when noise is strong. The relationship between the index value and the intensity of image restoration is as shown by an index value-intensity graph 509. The intensity of the image restoration process set based on the calculated index value is, for example, an image restoration process intensity graph 502.

  Similar to the first embodiment, the strength of the image restoration processing on both sides of the boundary is interpolated, and the strength of the image quality improvement processing is, for example, as shown in the image quality improvement processing strength graph 503.

  In addition, the structure 302 is also shown in another image frame 504 of the acquired moving image 106 shown in FIG. 6B, and the defect 303 exists on the structure 302 on the line. It is assumed that noise due to radiation is also superimposed on the image frame 504. Different image frames mean different imaging timings. There is a possibility that the magnitude of noise to be superimposed is different when the imaging timing is different.

  As in the first embodiment, description will be made using only the AA ′ cross section of the image frame 504. The pixel values of the AA ′ cross section of the image frame 504 are as shown in a pixel value graph 505, for example. Similar to the above example, the index value is set as the noise level, and is calculated for each divided moving image of the AA ′ section. The calculation result is as shown in an index value graph 506, for example.

  The intensity of the image restoration process set based on the calculated index value is, for example, an image restoration process intensity graph 507. Similar to the first embodiment, the strength of the image restoration processing on both sides of the boundary is interpolated, and the strength of the image quality improvement processing is, for example, as shown in the image quality improvement processing strength graph 508.

  Since different noises are superimposed on the image frame 301 and the image frame 504, the index value calculation results are different, and the image quality improvement processing intensity is also different. As described above, it is possible to set the divided moving images having different image frames by changing the strength of the image restoration processing.

  Similarly, when the index value is the degree of blur, it is possible to set the index value calculation and the strength of the image restoration process for each divided moving image. The degree of blur is, for example, a PSF (point spread function) obtained by performing a cepstrum analysis generally known for divided moving images.

  As described above, since the inspection object is imaged while moving the camera, the distance between the camera and the inspection object changes for each image frame in the moving image. In addition, since the inspection object has a structure having a depth, the distance between the camera and the inspection object varies depending on the position on each image frame. As a result, the degree of blurring of the image changes for each image frame or for each position on each image frame, but the strength of the image restoration process can be set according to the change in the degree of blurring for each divided moving image.

  With such a method, it is possible to set the strength of image quality improvement processing according to the number of structures and defects, according to the size of noise, or according to the size of blurring of moving images.

(Embodiment 4)
The fourth embodiment is different from the first and second embodiments in that the dividing method into divided moving images in creating high-quality moving images is different from the dividing method into divided moving images in calculating index values. The configuration and the image processing in the image processing apparatus are the same as those in the first embodiment.

  The image quality improvement processing should be performed according to the number of structures and defects, according to the size of noise, or according to the size of blur of moving images. Therefore, it becomes a problem to divide into divided regions suitable for creating high-quality moving images.

  The division into divided moving images used in the calculation of the index value is a division method performed before the calculation of the index value, and thus is a division method that is unrelated to the magnitude of the index value. On the other hand, division into divided moving images in creation of a high-quality moving image should be performed based on the index value.

  Therefore, in the present embodiment, the dividing method into divided moving images in creating a high-quality moving image is made different from the dividing method into divided moving images in calculating an index value. As a result, it is possible to divide into divided regions suitable for creating high-quality moving images.

<How to divide into divided videos>
With reference to FIG. 7, a method of dividing into divided moving images by the inspection apparatus according to the fourth embodiment of the present invention will be described. FIG. 7 is an explanatory diagram for explaining a method of dividing into divided moving images by the inspection apparatus according to the fourth embodiment of the present invention.

  In FIG. 7, in the calculation of the index value, for example, the division of the image frame 301 into the divided areas is divided into a lattice shape to create a divided moving image 401. The divided moving image includes a divided moving image 601 in which the structure 302 exists and a divided moving image 602 corresponding to the background.

  When the index value is, for example, the degree of existence of a structure or a defect and is calculated for each divided moving image, the index value distribution graph 603 is obtained, for example. One memory on the x and y axes of the index value distribution graph 603 corresponds to one divided moving image. Since structures and defects have various shapes, they do not always fit neatly into the divided areas used in calculating the index value.

  Therefore, using the degree of existence of the structure or the defect, a plurality of divided moving images having a similar degree of existence are collectively used as a divided divided moving image. For example, on the index value distribution graph 603, the index value 604 of the divided moving image where the structure exists is large, and the index value 605 of the divided moving image corresponding to the background is small.

  Therefore, in the divided moving image creation 606 in the creation of the high-quality moving image, the divided moving images having a large index value are collectively referred to as a divided divided moving image 607. In the figure, the summary divided moving image 607 is indicated by a region surrounded by a white line, and is composed of a divided moving image in which a structure or a defect exists. In addition, the divided moving images having a small index value are collectively set as another divided divided moving image 608. In FIG. 7, it is indicated by a region outside the white line, and consists of a divided moving image corresponding to the background. Thereby, the divided moving images having similar index values can be collectively subjected to the same image quality improvement processing.

  Alternatively, for example, since structures and defects have various shapes, they may exist only in a part of the divided region. Therefore, for example, a portion having a different color from the surroundings is obtained as a portion where a structure or a defect exists based on color information, and is set as a divided moving image.

  For example, there is a divided moving image 609 in which a defect 303 exists in the image frame 301. The moving image 610 which expanded this is shown. The defect 303 exists only in a part of the divided moving image. The part where the defect exists is a part that the user particularly wants to see in the divided moving image. Therefore, for example, using the color information that the defect 303 is blacker than the surroundings, a portion where the defect exists is further divided from the divided moving images to obtain another divided moving image 611.

  As a result, a plurality of divided moving images used in the calculation of the index value can be combined into a divided moving image including a structure or a defect. Further, the divided moving image used in the calculation of the index value can be further divided so that only a portion where a structure or a defect exists is made a divided moving image.

(Embodiment 5)
The fifth embodiment is the same as the first and second embodiments in that the strength of image restoration is the size of the blur function used in the image restoration processing or the number of repetitions of the image restoration processing. Image processing and the like in the processing apparatus are the same as those in the first embodiment.

  When image restoration processing is performed as image quality improvement processing, it is a problem to appropriately set the strength of image quality improvement processing using index values. The main factor that determines the strength of image restoration is the size of the blur function used in the image restoration processing or the number of repetitions of the image restoration processing.

  Therefore, in the present embodiment, the magnitude of the blur function used in the image restoration process or the number of repetitions of the image restoration process is used as the image restoration strength. Thereby, it is possible to appropriately set the strength of the image quality improvement processing according to the change of the index value.

<Indicator value calculation and image quality improvement processing intensity setting>
Next, referring to FIG. 8, description will be given of index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the fifth embodiment of the present invention. FIG. 8 is an explanatory diagram for explaining index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the fifth embodiment of the present invention.

  In the present embodiment, the setting of the strength of the image restoration processing is, for example, the strength of the image quality improvement processing is set to the magnitude of the blur function. When the presence of structures and defects is large, the blurring function is increased to enhance image restoration.

  In FIG. 8, a structure 302 is shown in an image frame 301 with the acquired moving image 106, and a defect 303 exists on the structure 302 on the line. It is assumed that noise due to radiation is superimposed on the image frame 301. The example of dividing into divided areas is an example of dividing into a lattice shape. As in the first embodiment, description will be made using only the AA ′ cross section of the image frame 301.

  The index value is the degree of existence of the structure or defect, and the index value calculation result is as shown in the index value graph 306. For example, the strength of the image quality improvement processing is set as the number of image restoration iterations. When the presence of structures and defects is large, the image restoration is strengthened by increasing the number of iterations. The relationship between the index value and the intensity of image restoration is as shown by an index value-intensity graph 703.

  Since the number of iterations of the image restoration process is set as an integer, the intensity changes on the step. The intensity of the image restoration process set based on the calculated index value is, for example, an image restoration process intensity graph 701. Similar to the first embodiment, the intensity of the image restoration process on both sides of the boundary is interpolated, and the intensity of the image restoration process is, for example, an image restoration process intensity graph 702. Thereby, it is possible to appropriately set the strength of the image restoration process in accordance with the change of the index value.

(Embodiment 6)
In the sixth embodiment, the degree of noise is displayed on the screen or stored in the storage device in the third embodiment, and the configuration of the inspection apparatus, the image processing in the image processing apparatus, and the like are described in the third embodiment. Same as 1.

  Since the image quality improvement processing is performed on the acquired moving image, the noise of the moving image to be displayed and stored is different from that of the original acquired moving image, and it is necessary to grasp the original noise.

  In the present embodiment, the noise level calculated as the index value is displayed on the screen by the GUI 204 or stored in the storage device 203 so that the original noise can be grasped.

<Example of screen display>
With reference to FIG. 9, an example of a screen display by GUI of the inspection apparatus according to the sixth embodiment of the present invention will be described. 9A and 9B are explanatory diagrams for explaining a screen display example by the GUI of the inspection apparatus according to the sixth embodiment of the present invention. FIG. 9A shows a screen display example, and FIG. 9B shows a noise level. Shows an enlarged view of the dialog.

  As shown in FIG. 9A, a high-quality moving image 801 is displayed on the GUI 204. For example, a dialog 802 is displayed on the GUI 204. The dialog 802 displays the noise degree value 803 of each image frame as shown in FIG. The dialog 802 may display a noise level gauge 804.

  Further, the dialog 802 displays a button 805 for labeling and saving the high-quality moving image 801 displayed on the GUI 204. By clicking a button 805 while a high-quality moving image is displayed on the GUI 204, the moving image displayed on the GUI 204 is given a noise level as a label and stored in the storage device 203.

  As a result, the user can grasp the degree of noise at the inspection location during or after the inspection.

(Embodiment 7)
In the seventh embodiment, the radioactivity damage degree of the camera calculated from the degree of blur in the sixth embodiment is displayed on the screen or stored in the storage device. The configuration of the inspection device and the image processing device are described in the seventh embodiment. The image processing and the like in are the same as in the first embodiment.

  In an environment with a lot of radiation, the electronic circuitry in the camera is damaged and its function is gradually lost. However, although the degree of damage and life of the camera are not known, camera damage appears as a phenomenon in which the degree of blur of the acquired moving image gradually increases.

  In the present embodiment, the degree of blur is calculated as the index value. Therefore, the radioactivity damage degree of the camera is estimated from the degree of blur, and the estimated radioactivity damage degree is displayed on the screen by the GUI 204 or stored in the storage device 203.

  As a result, the user can grasp the radioactivity damage degree of the camera at the time of or after the inspection, and can assist in the determination of the camera life and the replacement time.

<Estimation of radiation damage>
Next, estimation of the radioactivity damage degree of the inspection apparatus according to Embodiment 7 of the present invention will be described with reference to FIG. FIG. 10 is an explanatory diagram for explaining estimation of the radioactivity damage degree of the inspection apparatus according to the seventh embodiment of the present invention.

  In the present embodiment, the acquired moving image is divided as in the first embodiment. The index value is set as the degree of blur, and the index value is calculated for each divided video. Since the degree of blur increases as the radioactivity damage degree increases, the relationship between the index value and the radioactivity damage degree of the camera is as shown in an index value-damage degree graph 901 in FIG.

  The radioactivity damage degree of the camera is estimated from the index value calculated from the index value-damage degree graph 901. For example, if the index value is blur d902, the damage degree D903 is obtained. The estimated damage degree is displayed on the screen by the GUI 204 or stored in the storage device 203.

<Example of screen display>
With reference to FIG. 11, a screen display example using a GUI of the inspection apparatus according to the seventh embodiment of the present invention will be described. 11A and 11B are explanatory diagrams for explaining a screen display example by the GUI of the inspection apparatus according to the seventh embodiment of the present invention. FIG. 11A is a screen display example, and FIG. An enlarged view of the dialog to be displayed is shown.

  As shown in FIG. 11A, a high-quality moving image 801 and a dialog 802 are displayed on the GUI 204 as in the sixth embodiment. In addition, a dialog 1002 is displayed on the GUI 204. The dialog 1002 displays a value 1003 of the radiation damage degree as shown in FIG. The dialog 1002 may display a gauge 1004 of the radioactive damage level.

  Further, the dialog 1002 displays a button 1005 for labeling and saving the high-quality moving image 801 displayed on the GUI 204. By clicking a button 1005 in a state where a high-quality moving image is displayed on the GUI 204, the moving image displayed on the GUI 204 is given a radiological damage degree as a label and stored in the storage device 203.

  As a result, the user can grasp the radioactivity damage degree of the camera at the time of or after the inspection, and can assist in the determination of the camera life and the replacement time.

  The index value-damage degree graph 901 may be created by calculating the degree of blur using a camera whose damage degree is known in advance.

(Embodiment 8)
In the eighth embodiment, an object to be inspected in an environment affected by radiation is captured by a camera having a number of pixels larger than the number of pixels displayed on the screen or the number of pixels stored, and a moving image of the object to be inspected is acquired. To divide into multiple image frames, or to divide each image frame into multiple divided areas to create a divided movie, so that the signal component is saved after reduction using the reduction ratio used in the reduction process, Set image quality improvement processing or reduction processing, apply the image quality improvement processing set for each divided video to create a high-quality video, and apply the reduction processing set for each divided video from the high-quality video to high-quality video Creates a reduced video, displays the high-quality reduced video on the screen, and stores the high-quality reduced video in the storage device. Configuration of the inspection device other than the camera, image processing in the image processing device, etc. Is real Is the same as that of Embodiment 1.

  In the inspection of a power plant or the like, a moving image used for the inspection is stored. The moving image format used here is the number of pixels in which an image acquired by a camera used in a conventional inspection just fits. There may be a case where the resolution is insufficient with this number of pixels.

  Therefore, in the present embodiment, a moving image of the inspection object is acquired by imaging with a camera having a larger number of pixels than the number of screen display pixels or the number of storage pixels. On the other hand, since the acquired moving image does not fit in the moving image format to be stored, it needs to be reduced. If the image is simply reduced, the resolution is reduced due to the decrease in the number of pixels. Therefore, the advantage of imaging with a camera with a large number of pixels cannot be utilized, and the same as in the case of imaging with a camera used in a conventional inspection.

  Therefore, the acquired moving image is divided into a plurality of divided moving images so that necessary signal components are saved after the reduction, and image quality improvement processing and reduction processing are performed for each divided moving image according to the reduction rate.

  As a result, a high-quality moving image with improved resolution can be obtained.

  Here, the movie format to be saved is different from the movie format used in Japan, the United States, etc. and the movie format used in Europe, etc., and there is a possibility that a standard with more pixels will be used in the future. It is necessary to deal with them. It shall correspond to the NTSC standard currently used in Japan and the United States, the PAL standard used in Europe and the like, or the HDTV standard that may be used in the future.

  For example, if the conventional TV monitor or DVD video format standard is NTSC, there is a possibility of displaying or saving to it, so that the video obtained with a camera having a larger number of pixels than the NTSC standard is NTSC. Since it will be necessary to reduce it to a standard, this is addressed.

  In addition, since the strength of the image quality improvement process changes discontinuously at the boundary of the divided areas, the image changes unnaturally at the boundary of the divided areas, so it is necessary to prevent the image from changing unnaturally at the boundary of the divided areas. is there.

  Therefore, in the present embodiment, the intensity is adjusted and set so as to continuously change.

  As a result, it is possible to suppress the image from changing unnaturally at the boundary between the divided regions.

<Indicator value calculation and image quality improvement processing intensity setting>
Next, referring to FIG. 12, description will be given of index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the eighth embodiment of the present invention. FIG. 12 is an explanatory diagram for explaining index value calculation and image quality improvement processing intensity setting of the inspection apparatus according to the eighth embodiment of the present invention.

  In FIG. 12, a structure 302 is shown in an image frame 301 with the acquired moving image 106, and a defect 303 exists on the structure 302 on a line. The division into the divided areas is an example in which the division is performed in a lattice shape as in the second embodiment. Similarly to the first embodiment, only the AA ′ section of the image frame 301 will be described.

  The pixel values of the AA ′ cross section of the image frame 301 are as shown in the pixel value graph 305, for example.

  For example, the degree of existence of a structure or a defect is calculated for each divided moving image, and the strength of image quality improvement processing for a divided moving image having a large degree of existence is increased. The index value calculation result is as shown in an index value graph 306, for example.

  The image quality improvement processing is, for example, image restoration processing, and processing for deconvolution of the blur function. The strength of the image quality improvement processing is the magnitude of the blur function. At this time, the strength of the image quality improvement processing is set using the reduction ratio used in the reduction processing.

  The relationship between the index value and the intensity of image restoration is as shown by an index value-intensity graph 1101. The strength of image quality improvement processing is increased in a divided moving image with a large degree of existence of structures or defects. For example, when the reduction ratio is 1/2, the strength of the image quality improvement process is set to double. In the index value-intensity graph 1101, the strength indicated by the thin line is set. The intensity of the image restoration process is, for example, an image restoration process intensity graph 1102.

  In the divided moving image 1103 with a large index value, the strength shown by the solid line is set from the strength shown by the dotted line. Further, the image restoration processing intensity on both sides of the boundary is interpolated to obtain an image restoration processing intensity graph 1104.

  Here, the reduction ratio is determined by the number of pixels of the camera and the number of screen display pixels or the number of storage pixels, and is assumed to be given in advance by user input or calculation. FIG. 13 shows an example of a screen display for performing an inspection. FIGS. 13A and 13B are explanatory diagrams for explaining a screen display example by the GUI of the inspection apparatus according to the eighth embodiment of the present invention, FIG. 13A shows a screen display example, and FIG. 13B shows a reduction ratio. Shows an enlarged view of the dialog.

  As in the seventh embodiment, a high-quality moving image 801, a dialog 802, and a dialog 1002 are displayed on the GUI 204. In addition, a dialog 1202 is displayed on the GUI 204.

  In the dialog 1202, as shown in FIG. 13B, the camera pixel number input / display field 1203, the screen display pixel number input / display field 1204, the storage pixel number input / display field 1205, the reduction rate input / display field 1205, and the like. A display field 1206 is provided.

  The user inputs the number of camera pixels, the number of screen display pixels, the number of stored pixels, and the reduction ratio in each input field. Here, the reduction ratio may be automatically calculated by dividing the smaller of the screen display pixel number and the storage pixel number by the camera pixel number and displayed in the reduction ratio input / display field 1206.

  Next, a signal enhancement process, which is an image quality improvement process, is performed using the strength of the image quality improvement process set for each divided area, which is a divided video, to create a high-quality video. Next, the high-quality video is reduced at the reduction rate to create a high-quality video.

  Alternatively, for example, the degree of existence of a structure or a defect is calculated for each divided area in the same manner as described above, and the strength of image quality improvement processing for a divided moving image with a high degree of existence is increased. The image quality improvement process is an image restoration process, and the intensity of the image quality improvement process is the intensity of the image quality restoration process.

  Further, the reduction process is set using the reduction ratio. For example, when the reduction ratio is ½, if there is a pixel having a large presence of a structure or a defect within 2 pixels, the pixel is selected to be reduced. Next, signal enhancement processing is performed using the strength of image quality improvement processing set for each divided region to create a high-quality moving image. Next, the reduction process set for the high quality moving image is performed to create a high quality reduced moving image.

  As a result, it is possible to obtain a high-quality reduced moving image in which the structure or defect is stored by performing signal enhancement or reduction processing with the intensity according to the degree of existence of the structure or the defect and the intensity according to the reduction ratio. It becomes possible.

  Alternatively, the image quality improvement processing is, for example, noise suppression processing and processing that is added to the past multiple image frames. The strength of image quality improvement processing is the number of frames added. For example, the noise level is calculated for each divided moving image. A divided moving image with a large noise degree increases the number of frame additions. At this time, the frame addition number is set using the reduction ratio used in the reduction process.

  If the reduction ratio is small, noise suppression due to reduction can be expected, so the number of frames added is adjusted. For example, when the reduction ratio is ½, the frame addition number is adjusted to ½. Next, noise suppression processing is performed using the frame addition number set for each divided moving image to create a high-quality moving image.

(Embodiment 9)
In the ninth embodiment, the division into divided regions for each image frame is a grid-like division in the eighth embodiment, and the configuration of the inspection apparatus, the image processing in the image processing apparatus, and the like are described in the embodiment. It is the same as 8.

<Division into divided areas for creating a divided video>
With reference to FIG. 14, division into divided areas for creating a divided moving image by the inspection apparatus according to the ninth embodiment of the present invention will be described. FIG. 14 is an explanatory diagram for explaining division into divided areas for creating a divided moving image by the inspection apparatus according to the ninth embodiment of the present invention.

  In the present embodiment, as shown in FIG. 14, in the division into divided areas, the divided moving image 1301 is created by dividing the image frame 301 into a plurality of grid-like divided areas. The boundary 1302 of the divided area is indicated by vertical and horizontal dotted lines in the drawing. One section surrounded by a dotted line is one divided moving image.

  In this way, the index value calculation unit is given as a simple lattice shape, and after calculating the index value, the index value calculation unit is determined in order to determine the divided region for image quality improvement processing according to the index value. It is given in a grid pattern. As a result, it is possible to perform division into divided areas necessary for calculating the index value.

(Embodiment 10)
The tenth embodiment is a high-resolution camera having a larger number of pixels than the cameras conventionally used in the eighth and ninth embodiments. The configuration of the inspection apparatus and the image processing in the image processing apparatus are as follows. This is the same as in the eighth and ninth embodiments.

  The defect to be detected is a size of 1 mil width or more, and when the image is taken with a 300,000 pixel camera that has been used in the past, depending on the distance between the camera and the object, the size of the sub-pixel on the acquired moving image, Since the visibility is poor as it is, it is necessary to bring the camera closer. In order to improve the reliability of the inspection, it is desirable that the defect to be detected on the acquired moving image has a size of about 1 pixel or more.

  Therefore, in the present embodiment, a high-resolution camera (for example, 1 million pixels or more) having a larger number of pixels than the conventionally used 300,000 pixel camera is used.

  As a result, the resolution about twice that of the prior art is provided, and a defect with a width of 1 mil or more becomes about 1 pixel or more on the acquired moving image without approaching the camera, so that the defect can be easily detected. It becomes possible.

<Example of imaging of inspection object>
With reference to FIG. 15, an imaging example of the inspection object of the inspection apparatus according to Embodiment 10 of the present invention will be described. FIG. 15 is an explanatory diagram for explaining an imaging example of the inspection object of the inspection apparatus according to the tenth embodiment of the present invention.

  As shown in FIG. 15, for example, there is a place where a defect 303 exists in the image frame 301. When an image is captured without approaching the object with a 300,000 pixel camera, an enlarged image of a portion where the defect 303 exists is an image indicated by 1303 in FIG. Each square area surrounded by a dotted line is one pixel. The defect 303 has a vertical streak shape and has a width of less than one pixel.

  In addition, when an image is captured by a camera with 1.2 million pixels, an image obtained by enlarging a portion where the defect 303 exists is an image indicated by 1304 in FIG. Each square area surrounded by a dotted line is one pixel. In this case, the defect 303 is about 1 pixel wide.

  Thereby, it becomes possible to detect a defect stably.

(Embodiment 11)
In the eleventh embodiment, in the first to tenth embodiments, the moving image captured by the camera is displayed on the GUI 204 at the same time as the high-quality moving image obtained by image processing, or stored in the storage device 203. The configuration and the image processing in the image processing apparatus are the same as those in the first embodiment.

  If only high-quality video is displayed and saved, the user cannot grasp the noise, contrast, and blur level of the original video. It is effective to display and present it to the user.

  Therefore, in the present embodiment, in order to make it possible to grasp the state of the original moving image, the moving image captured by the camera is displayed and stored simultaneously with the high-quality moving image.

<Example of screen display>
With reference to FIG. 16, an example of a screen display by GUI of the inspection apparatus according to the eleventh embodiment of the present invention will be described. 16A and 16B are explanatory diagrams for explaining a screen display example by the GUI of the inspection apparatus according to the eleventh embodiment of the present invention. FIGS. 16A and 16B are screen display examples, and FIG. The enlarged view of the dialog for switching a display is shown.

  As shown in FIG. 16A, a high-quality moving image 801, a dialog 802, a dialog 1002, and a dialog 1202 are displayed on the GUI 204, as in the eighth embodiment. In addition, a dialog 1402 is displayed on the GUI 204.

  As shown in FIG. 16C, the dialog 1402 is provided with a display image switching button 1403 for switching between the captured image, the processing result, and the two screens.

  When the switching button 1403 is a captured image, the high-quality moving image 801 on the GUI 204 is switched to a captured image. When the switching button 1403 is a processing result, the high-quality moving image 801 is switched to a processing result image. As shown in FIG. 16B, the captured image 1404 and the processing result image 1405 are displayed on the GUI 204 at the same time.

  As a result, the original moving image can be compared with the high-quality moving image, and the noise, contrast, and degree of blur of the original moving image can be easily grasped.

(Embodiment 12)
In the twelfth embodiment, the acquired moving image is trimmed to the number of pixels that can be accommodated in the number of screen display pixels or the number of storage pixels in the eighth embodiment, and the configuration of the inspection apparatus and the image processing in the image processing apparatus These are the same as in the first embodiment.

  If you take an image of the inspection object by capturing with a camera with more pixels than the number of storage pixels, and do not reduce the acquired movie, it may not fit on the screen display pixel number or storage pixel number. It is necessary to reduce the acquired moving image other than the reduction process so as to be within the number of screen display pixels or the number of storage pixels.

  Therefore, in the present embodiment, the acquired moving image is trimmed to the number of pixels that can be accommodated in the number of screen display pixels or the number of storage pixels to reduce the size.

  This makes it possible to obtain a high-quality moving image that can fit within the number of screen display pixels or the number of storage pixels.

  Further, in the trimming, it is important to select a portion in the acquired moving image to trim, and when trimming, the user should select what he / she wants to see. For example, what the user wants to see is a structure or a defect.

  Therefore, in this embodiment, an index value is calculated for each divided region, and trimming is performed based on the index value. For example, the degree of existence of a structure or a defect is calculated as an index value for each divided region. Based on the calculated index value, for example, a trimming region is selected and trimmed with the number of pixels that can be accommodated in the number of screen display pixels or the number of storage pixels around a divided region where the degree of existence of a structure or a defect is the largest.

<Example of trimming>
An example of trimming of the inspection apparatus according to the twelfth embodiment of the present invention will be described with reference to FIGS. 17 to 19 are explanatory diagrams for explaining an example of trimming of the inspection apparatus according to the twelfth embodiment of the present invention. FIG. 17 is an example in which trimming is performed centering on a divided region where the degree of existence of the defect is the largest. 18 shows an example in which the vicinity of the center of the image is set as a trimming location, and FIG. 19 shows an example in which the user designates the trimming location on the GUI.

  In FIG. 17, a defect 303 exists on the stripe in the image frame 301 with the acquired moving image. As described in the first embodiment and the like, the presence of a structure or a defect is the highest at a location where there is a defect, and therefore the trimming location 1501 is selected centering on this.

  FIG. 18 is an example in which the center of the screen is set as the center of the trimming location 1601 on the assumption that the user will see the location he wants to see at the center of the screen.

  In FIG. 19, as shown in FIG. 19A, the user designates an arbitrary location 1702 as a trimming location on the GUI 204 with the mouse cursor 1701 or the like. Further, as shown in FIG. 19B, the user may designate a corner with the mouse cursor 1703 or the like on the GUI 204 and designate an arbitrary rectangular area 1704 as the attention area.

  As a result, guidelines for trimming can be obtained and an effective trimming region can be selected.

  As mentioned above, the invention made by the present inventor has been specifically described based on the embodiment. However, the present invention is not limited to the embodiment, and various modifications can be made without departing from the scope of the invention. Needless to say.

  The present invention relates to an inspection method and an inspection apparatus that perform inspection by acquiring an image with a camera, and can be widely applied to apparatuses and systems that require high image quality such as improvement in resolution of an image acquired with a camera.

  111: High-quality video, 112: Split video, 113: Index value related to the strength of image quality improvement processing, 114: Split video, 115: Structure, 116: Defect, 117 ... B area, 118 ... C area, 119 ... A Area: 120 ... B movie, 121 ... High resolution high quality movie, 122 ... Reduced C movie, 123 ... Reduced high resolution high quality movie, 124 ... Trimming A movie, 125 ... Zoom high quality movie, 201 ... Camera, 202 ... Image Processing device 203 ... Storage device 204 ... GUI 205 ... Inspection object 206 ... Lighting 207 ... Cable 2021 ... Image input unit 2022 ... Image memory 2023 ... Division video setting unit 2024 ... Image quality improved image reduction Unit, 2025 ... image output unit, 2026 ... index value calculation unit, 2027 ... image quality improvement divided moving image setting unit, 2028 ... image quality improvement setting unit, 2029 ... image Reduction setting unit, 301 ... image frame, 302 ... structure, 303 ... defect, 304 ... divided video, 305 ... pixel value graph, 306 ... index value graph, 307 ... image restoration processing intensity graph, 308 ... divided region boundary, 309 ... Image restoration processing intensity graph, 310 ... Division area boundary, 311 ... Index value-intensity graph, 401 ... Division video, 402 ... Division area boundary, 501 ... Index value graph, 502 ... Image restoration processing intensity graph, 503 Image quality improvement processing intensity graph, 504 ... Another image frame, 505 ... Pixel value graph, 506 ... Index value graph, 507 ... Image restoration processing intensity graph, 508 ... Image quality improvement processing intensity graph, 509 ... Index value-intensity graph, 601: Split video, 602: Split video, 603: Index value distribution graph, 604: Index value of split video, 605: Finger of split video Value: 606: Creation of split video, 607: Summary split video, 608: Summary split video, 609 ... Split video, 610: Expanded video, 611: Split video, 701: Image restoration processing intensity graph, 702: Image restoration processing Intensity graph, 801 ... high-quality video, 802 ... dialog, 803 ... noise degree value, 804 ... noise degree gauge, 805 ... button, 901 ... index value-damage degree graph, 1002 ... dialog, 1003 ... radioactive damage degree 1004 ... Radio damage level gauge, 1005 ... button, 1101 ... index value-intensity graph, 1102 ... image restoration processing strength graph, 1103 ... divided moving image, 1104 ... image restoration processing strength graph, 1202 ... dialog, 1203. ... Camera pixel number input / display field 1204 ... Screen display pixel number input / display field 1205 ... Number of stored pixels / display field 1206 ... Reduction ratio input / display field, 1301 ... Division video, 1302 ... Division of division area, 1402 ... Dialog, 1403 ... Switch button, 1404 ... Captured image, 1405 ... Processing result Image, 1501 ... Trimming location, 1601 ... Trimming location, 1701 ... Mouse cursor, 1702 ... Trimming location, 1703 ... Mouse cursor, 1704 ... Arbitrary rectangular area.

Claims (14)

A camera that images the inspection object, an image processing device that acquires a moving image of the inspection object imaged by the camera and processes the moving image, a display device that displays the moving image processed by the image processing device, and the An inspection method in an inspection apparatus having a storage device for storing a moving image processed by an image processing apparatus,
The image processing device acquires a moving image of the inspection object imaged by the camera, divides the acquired moving image into a plurality of image frames, and divides each image frame into a plurality of divided regions to generate divided moving images. Create an index value related to the strength of image quality improvement processing for each divided video, set the strength of the image quality improvement processing according to the value of the index value for each divided video, Create a high-quality video, display the created high-quality video on the display device, store the high-quality video in the storage device ,
The index value is, the presence degree structures or defects in the split in the video, noise degree of the divided moving image or inspection method characterized by blur degree der Rukoto of the divided moving. A camera that images the inspection object, an image processing device that acquires a moving image of the inspection object imaged by the camera and processes the moving image, a display device that displays the moving image processed by the image processing device, and the An inspection method in an inspection apparatus having a storage device for storing a moving image processed by an image processing apparatus,
The image processing device acquires a moving image of the inspection object imaged by the camera, divides the acquired moving image into a plurality of image frames, and divides each image frame into a plurality of divided regions to generate divided moving images. Create an index value related to the strength of image quality improvement processing for each divided video, set the strength of the image quality improvement processing according to the value of the index value for each divided video, Create a high-quality video, display the created high-quality video on the display device, store the high-quality video in the storage device,
When creating the high-quality video by the image processing device, the division into the divided videos for performing the image quality improvement processing is performed in a region different from the division into the divided videos in the calculation of the index value. Inspection method characterized by The inspection method according to claim 1 or 2 ,
2. The inspection method according to claim 1, wherein the division into the divided areas for each of the image frames by the image processing device is a grid-like division. In the inspection method according to any one of claims 1 to 3 ,
Intensity of the image quality improvement process, inspection method, wherein the image quality improvement size of the blur function used in image restoration processing to be processed as a process, or a number of iterations of the image restoration processing. In the inspection method according to any one of claims 1 to 4 ,
An inspection method, wherein the image processing device causes the display device to display a noise level of a moving image of the inspection object imaged by the camera, and stores the noise degree in the storage device. In the inspection method according to any one of claims 1 to 5 ,
The image processing apparatus causes the display device to display the radioactivity damage degree calculated from the degree of blur of the moving image of the inspection object imaged by the camera, and to store it in the storage device. Inspection method. In the inspection method according to any one of claims 1 to 6 ,
By the image processing apparatus, the videos captured by the camera, with video which has been subjected to the image quality improvement treatment, the display device to be displayed, and wherein the video taken by the camera can be stored in the storage device Inspection method. A camera for imaging the inspection object;
An image processing apparatus for acquiring a moving image of the inspection object imaged by the camera and processing the moving image;
A display device for displaying a moving image processed by the image processing device;
A storage device for storing the moving image processed by the image processing device,
The image processing device acquires a moving image of the inspection object imaged by the camera, divides the acquired moving image into a plurality of image frames, and divides each image frame into a plurality of divided regions to divide the moving image. An index value related to the strength of image quality improvement processing is calculated for each of the divided videos, and the image quality improvement processing is performed by setting the strength of the image quality improvement processing according to the index value for each of the divided videos. Creating a high-quality video, displaying the created high-quality video on the display device, storing the high-quality video in the storage device ,
The index value, the presence degree of a structure or a defect in the divided video noise degree of the divided moving image or the divided video inspection device according to claim blur degree der Rukoto of. A camera for imaging the inspection object;
An image processing apparatus for acquiring a moving image of the inspection object imaged by the camera and processing the moving image;
A display device for displaying a moving image processed by the image processing device;
A storage device for storing the moving image processed by the image processing device,
The image processing device acquires a moving image of the inspection object imaged by the camera, divides the acquired moving image into a plurality of image frames, and divides each image frame into a plurality of divided regions to divide the moving image. An index value related to the strength of image quality improvement processing is calculated for each of the divided videos, and the image quality improvement processing is performed by setting the strength of the image quality improvement processing according to the index value for each of the divided videos. Creating a high-quality video, displaying the created high-quality video on the display device, storing the high-quality video in the storage device,
When creating the high-quality video by the image processing device, the division into the divided videos for performing the image quality improvement processing is performed in a region different from the division into the divided videos in the calculation of the index value. Inspection device characterized by The inspection apparatus according to claim 8 or 9,
The inspection apparatus according to claim 1, wherein the division into the divided areas for each of the image frames by the image processing apparatus is a grid-like division. In the inspection device according to any one of claims 8 to 10,
The strength of the image quality improvement process is the magnitude of a blur function used in the image restoration process processed as the image quality improvement process or the number of repetitions of the image restoration process. The inspection apparatus according to any one of claims 8 to 11,
The image processing device causes the display device to display a noise level of a moving image of the inspection object imaged by the camera and store the noise degree in the storage device. In the inspection apparatus according to any one of claims 8 to 12,
The image processing device displays the radioactivity damage degree of the camera calculated from the degree of blur of the moving image of the inspection object imaged by the camera on the display device and stores it in the storage device. Inspection device. The inspection apparatus according to any one of claims 8 to 13,
The image processing device displays the moving image captured by the camera together with the moving image subjected to the image quality improvement processing on the display device, and stores the moving image captured by the camera in the storage device. apparatus.