Smoke concentration evaluation device, smoke concentration evaluation system, smoke concentration evaluation method, and program

Abstract

This smoke concentration evaluation device comprises: an image acquisition unit that acquires a plurality of images of a region including a smoke discharge unit that discharges smoke, the plurality of images being captured at time intervals; an image processing unit that identifies, on the basis of a difference between the images, a pixel of a portion in which smoke appears, from among a plurality of pixels constituting the images; a luminance acquisition unit that acquires the luminance of the pixel of the portion in which smoke appears; and an opacity acquisition unit that acquires information relating to the opacity of the images on the basis of the luminance of the pixel of the portion in which smoke appears.

Description

Smoke density evaluation apparatus, smoke density evaluation system, smoke density evaluation method, and program

[0001] The present disclosure relates to a smoke density evaluation apparatus, a smoke density evaluation system, a smoke density evaluation method, and a program. The present application claims priority based on Japanese Patent Application No. 2025-029046 filed in Japan on February 26, 2025, the content of which is incorporated herein by reference.

[0002] Patent Document 1 discloses a smoke detection apparatus that detects the generation of smoke from an image captured by a camera. This smoke detection apparatus sets a detection region in a captured image, and detects the generation of smoke in the detection region based on moving pixels detected in the detection region by performing frame difference processing on the image.

[0003] Japanese Unexamined Patent Publication No. 2008-46917

[0004] Incidentally, there are cases where it is required to detect the density of smoke discharged from a combustion apparatus. However, although the configuration described in Patent Document 1 can detect whether smoke is generated or not, it cannot evaluate the smoke density.

[0005] The present disclosure has been made to solve the above problems, and an object of the present disclosure is to provide a smoke density evaluation apparatus, a smoke density evaluation system, a smoke density evaluation method, and a program that can effectively evaluate smoke density.

[0006] In order to solve the above problems, the smoke density evaluation apparatus according to the present disclosure includes: an image acquisition unit that acquires a plurality of images of a region including a smoke discharge part that discharges smoke, the images being captured at time intervals; an image processing unit that specifies pixels of a portion where the smoke is captured among a plurality of pixels constituting the image based on a difference between the plurality of images; a luminance acquisition unit that acquires luminance of the pixels of the portion where the smoke is captured; and an opacity acquisition unit that acquires information related to opacity of the image based on the luminance of the pixels of the portion where the smoke is captured.

[0007] The smoke density evaluation system according to the present disclosure includes: a camera that captures an image of a region including a smoke discharge part that discharges smoke; and the smoke density evaluation apparatus as described above.

[0008] The smoke concentration evaluation method according to this disclosure includes the steps of: acquiring a plurality of images of a region including a smoke exhaust unit that emits smoke, taken at time intervals; identifying pixels in the portion of the image in which smoke is captured, from among a plurality of pixels constituting the image, based on the difference between the plurality of images; acquiring the brightness of the pixels in the portion of the image in which smoke is captured; and acquiring information regarding the opacity of the image based on the brightness of the pixels in the portion of the image in which smoke is captured.

[0009] The program relating to this disclosure causes a computer to perform the following steps: acquiring a plurality of images of a region including a smoke exhaust unit that emits smoke, taken at time intervals; identifying pixels in the portion of the image in which smoke is captured, from among a plurality of pixels constituting the image, based on the difference between the plurality of images; acquiring the brightness of the pixels in the portion of the image in which smoke is captured; and acquiring information regarding the opacity of the image based on the brightness of the pixels in the portion of the image in which smoke is captured.

[0010] According to the smoke concentration evaluation apparatus, smoke concentration evaluation system, smoke concentration evaluation method, and program of this disclosure, the smoke concentration can be effectively evaluated.

[0011] This diagram shows the configuration of the smoke concentration evaluation system according to the first, second, and fourth embodiments of this disclosure. This diagram shows the hardware configuration of the smoke concentration evaluation device according to the embodiment of this disclosure. This diagram shows the functional configuration of the smoke concentration evaluation device according to the embodiment of this disclosure. This diagram shows an example of a grayscale image created by the smoke concentration evaluation device according to the first embodiment of this disclosure. This diagram shows an example of an image after frame difference processing by the smoke concentration evaluation device according to the first embodiment of this disclosure. This diagram shows an example of the calculation result of the opacity obtained by the smoke concentration evaluation device according to the embodiment of this disclosure. This flowchart shows the flow of the smoke concentration evaluation method according to the embodiment of this disclosure. This diagram shows an example of an extracted image to be extracted from an image in the smoke concentration evaluation device according to the second embodiment of this disclosure. This diagram shows an example of an image after frame difference processing by the smoke concentration evaluation device according to the second embodiment of this disclosure. This diagram shows the configuration of the smoke concentration evaluation system according to the third embodiment of this disclosure. This diagram shows an example of a grayscale image created by the smoke concentration evaluation device according to the third embodiment of this disclosure. This diagram shows an example of a grayscale image created by the smoke concentration evaluation device according to the fourth embodiment of this disclosure.

[0012] The following describes embodiments for implementing the smoke concentration evaluation apparatus, smoke concentration evaluation system, smoke concentration evaluation method, and program according to this disclosure, with reference to the attached drawings. However, this disclosure is not limited to these embodiments.

[0013] (Configuration of the smoke concentration evaluation system) As shown in Figure 1, the smoke concentration evaluation system 1A comprises a camera 2 and a smoke concentration evaluation device 3A. Here, the smoke concentration evaluation system 1A evaluates the concentration of smoke emitted from the smoke exhaust section 100. The smoke exhaust section 100 is, for example, a chimney that discharges exhaust gas from a combustion device (not shown) that burns fuel, such as a diesel engine for a generator or a boiler installed in a data center, hospital, factory, etc.

[0014] (Camera) Camera 2 photographs the area Z1 including the smoke exhaust unit 100 that discharges smoke. Camera 2 is installed in a location that can photograph the area Z1 including the smoke exhaust unit 100, such as on the roof of the building where the smoke exhaust unit 100 is installed. It is preferable to fix Camera 2 in place using appropriate stays or the like to suppress displacement due to wind, vibration, etc.

[0015] In this embodiment, camera 2 captures a video of the region Z1 including the smoke exhaust unit 100. In this embodiment, camera 2 captures a video at a preset number of frames per unit time. Camera 2 transmits the captured video data to the smoke concentration evaluation device 3A via wired communication means using a communication cable, or wireless communication means such as a mobile phone communication network, Wi-Fi, or Bluetooth.

[0016] (Hardware Configuration Diagram) Figure 2 is a diagram showing the hardware configuration of a smoke concentration evaluation device according to an embodiment of the present disclosure. As shown in Figure 2, the smoke concentration evaluation device 3A is a computer equipped with various hardware components such as a CPU 61, ROM 62, RAM 63, storage 64 such as an HDD (HARD DISK DRIVE), and a communication module 65.

[0017] (Functional Block Diagram) Figure 3 is a diagram showing the functional configuration of a smoke concentration evaluation device according to the present disclosure. The smoke concentration evaluation device 3A evaluates the smoke concentration from the smoke exhaust unit 100 based on a plurality of images transmitted from the camera 2 by having the CPU 61 execute a program that is stored in the device in advance. As shown in Figure 3, the smoke concentration evaluation device 3A includes an image acquisition unit 71, an image processing unit 72, a brightness acquisition unit 74, an opacity acquisition unit 75, and a result output unit 77.

[0018] The image acquisition unit 71 acquires video data of the region Z1, which includes the smoke exhaust unit 100 that emits smoke, transmitted from the camera 2 and captured at time intervals. In this embodiment, the image acquisition unit 71 divides the acquired video data into frames and acquires multiple images. In other words, the image acquisition unit 71 acquires data of multiple images captured at time intervals.

[0019] Figure 4 shows an example of a grayscale image obtained using the smoke concentration evaluation device according to the first embodiment of this disclosure. The image processing unit 72 performs grayscale processing on each of the multiple images taken at time intervals, and as shown in Figure 4, converts each of the multiple pixels constituting each image into a grayscale image P1 having, for example, 256 scale values ​​(scale value: 0 to scale value: 255).

[0020] The image processing unit 72 processes multiple grayscale images P1 to identify the pixels in portion A where smoke is visible among the multiple pixels that make up image P1. Based on the difference between the multiple images P1, the image processing unit 72 identifies the pixels in portion A where smoke is visible among the multiple pixels that make up image P1. In this embodiment, frame difference processing is performed between two images P1 acquired at different time intervals. Figure 5 is a diagram showing an example of an image after frame difference processing with the smoke density evaluation device according to the present disclosure. In this embodiment, the image processing unit 72 identifies (extracts) pixels that have changed between the scale value of each pixel that makes up image P1 in one frame and the scale value of each pixel that makes up image P1 in the frame immediately preceding the one, as shown in Figure 5. In other words, the image processing unit 72 identifies pixels where a change in scale value, i.e., brightness, has occurred between two images P1 taken at different time intervals. In Figure 5, pixels where a change in brightness has occurred are shown in white, and pixels where no change in brightness has occurred are shown in black. In image P2 obtained by frame difference processing, if black smoke is present, a change in brightness occurs at the location where black smoke is present due to the flow of black smoke discharged from the smoke exhaust unit 100. The image processing unit 72 identifies the portion A in image P2 where black smoke is present by identifying pixels where a change in scale value (brightness) has occurred through frame difference processing.

[0021] The image processing unit 72 may perform position correction between multiple images P before identifying the pixels of the portion A in which smoke is captured based on the difference between the multiple images P. For this purpose, feature points that serve as the basis for position correction are set in advance within the region Z1 captured in the image P1 obtained by photographing the region Z1 including the smoke exhaust unit 100. The feature points are parts within the region Z1 that can be easily recognized (extracted) by image processing in the image processing unit 72, for example, the corners of the roof of the building where the smoke exhaust unit 100 is installed. The image processing unit 72 extracts the pre-set feature points from each of the multiple images P1 that are the subject of difference processing (frame difference processing), and aligns the positions of the multiple images P1 based on the extracted feature points. This suppresses positional shifts between the multiple images P1 caused by strong winds, vibrations, etc.

[0022] The luminance acquisition unit 74 acquires the luminance of multiple pixels that make up image P. The luminance acquisition unit 74 acquires the scale value, i.e., luminance, of each pixel in the grayscale image P1 (see Figure 4) that corresponds to the pixel identified as part A where smoke is visible in image P2 obtained by frame difference processing.

[0023] The luminance acquisition unit 74 may correct the detected luminance based on an initial image of region Z1 taken in advance, in a non-emission state where no smoke is being emitted from the smoke exhaust unit 100. In this case, the image acquisition unit 71 acquires an initial image taken by the camera 2 when the combustion device is in a non-operational state and no smoke is being emitted from the smoke exhaust unit 100. The luminance acquisition unit 74 corrects the scale value (luminance) of each pixel by taking the difference between each of the multiple images P1 and each pixel of the initial image in a non-emission state from the smoke exhaust unit 100, and obtains the corrected luminance. The luminance acquisition unit 74 may further calculate the median or average value of the scale values ​​of the pixels in the background area and use the calculated median or average value to correct the luminance of the pixels in the entire image P.

[0024] The brightness acquisition unit 74 may convert the scale values ​​of multiple pixels in the portion A where the smoke is captured into the average of the scale values ​​of these multiple pixels. When the image processing unit 72 performs difference processing between multiple images P1, pixels where there is no change in scale value or the change in scale value is small may be affected by noise. In contrast, noise can be reduced by converting the scale values ​​of multiple pixels to the average value, a process known as averaging.

[0025] Furthermore, the brightness acquisition unit 74 may convert the scale values ​​of multiple pixels in part A where the smoke is visible to the smallest scale value among these multiple pixels. In this way, noise can also be reduced by converting the scale values ​​of multiple pixels in part A where the smoke is visible to the minimum value, a so-called minimization process.

[0026] The opacity acquisition unit 75 acquires information regarding the opacity of image P1 based on the luminance of multiple pixels in the grayscale image P1 that are in the portion A where smoke is visible, i.e., pixels where a change in scale value (luminance) has occurred. In this embodiment, the opacity acquisition unit 75 acquires information regarding the opacity of image P1 based on the corrected luminance corrected by the initial image in a state where no smoke is being emitted from the smoke exhaust unit 100. In this embodiment, the opacity of image P1 is calculated, for example, by the following formula (1). Here, Kd is the brightness of each pixel in part A where the smoke is visible, and is expressed as a grayscale value from 0 (black) to 255 (white). Tp is the total number of pixels in image P1 in this embodiment.

[0027] Figure 6 shows an example of the calculation result of the opacity obtained by the smoke concentration evaluation device according to the embodiment of this disclosure. The result output unit 77 outputs the calculation result of the opacity obtained by the opacity acquisition unit 75 to the outside. The result output unit 77 outputs the calculation result of the opacity, as shown in Figure 6, by displaying it on a monitor screen, printing it, transmitting it to an external communication terminal such as a smartphone or tablet, etc. Based on the outputted calculation result of the opacity, the user of the smoke concentration evaluation system 1A can evaluate the condition of the smoke discharged from the smoke exhaust unit 100, evaluate the operating state of the combustion device which is the source of the smoke from the smoke exhaust unit 100, evaluate the performance of the combustion device, etc.

[0028] (Procedure for Smoke Concentration Evaluation Method) Figure 7 is a flowchart showing the flow of the smoke concentration evaluation method according to the present disclosure. As shown in Figure 7, the smoke concentration evaluation method according to the present disclosure includes the steps of: acquiring a plurality of images S11; identifying pixels in the portion where smoke is captured S12; acquiring the brightness of pixels in the portion where smoke is captured S13; and acquiring information regarding the opacity of the images S14. The smoke concentration evaluation method in this embodiment may be repeatedly executed at predetermined intervals while the smoke concentration evaluation system 1A is operating based on a preset program. Furthermore, the smoke concentration evaluation method in this embodiment may be performed, for example, only when the combustion device (not shown) that discharges exhaust gas from the smoke exhaust unit 100 is starting up, when the combustion device is likely to emit black smoke.

[0029] In step S11, which involves acquiring multiple images, multiple images of the region Z1 including the smoke exhaust unit 100 are acquired, taken at time intervals. In this embodiment, the image acquisition unit 71 acquires video data of the region Z1 including the smoke exhaust unit 100, transmitted from the camera 2. The image acquisition unit 71 divides the acquired video data into frames and acquires data of multiple images taken at time intervals. The image acquisition unit 71 also acquires the total number of pixels of the multiple images from which data has been acquired.

[0030] In step S12, which identifies the pixels in the area where smoke is visible, first, the image processing unit 72 performs a grayscale conversion process on each of the multiple images acquired by the image acquisition unit 71. Next, the image processing unit 72 identifies the pixels in the area A where smoke is visible based on image P2 obtained by performing a difference process on the multiple grayscale images P1. In this embodiment, the image processing unit 72 performs a frame difference process between two images P1 acquired at different time intervals, and identifies pixels in which the pixel scale value changes between the two images P1 as the area A where black smoke is present.

[0031] Furthermore, in step S12, prior to identifying the pixels of the portion A in which the smoke is captured, the image processing unit 72 may perform position correction between multiple images P based on feature points that serve as a reference for position correction, which have been set in advance.

[0032] In step S13, which involves acquiring the brightness of pixels in part A where smoke is visible, the brightness acquisition unit 74 acquires the scale value, i.e., brightness, of the pixels in part A where smoke is visible in the grayscale image P1. In step S13 of this embodiment, the brightness acquisition unit 74 corrects the acquired brightness based on an image previously taken of the smoke exhaust unit 100 in a state where no smoke is being emitted. Alternatively, the brightness acquisition unit 74 may calculate the average or minimum value of the scale values ​​of multiple pixels in part A where smoke is visible, and convert the brightness of the pixels in part A where smoke is visible to the calculated average or minimum value.

[0033] In step S14, which involves acquiring information regarding the opacity of image P, the opacity acquisition unit 75 acquires information regarding the opacity of image P1 based on the brightness of the pixels in part A where the smoke is visible. The opacity acquisition unit 75 calculates the opacity of image P1 based on the brightness of multiple pixels in part A where the smoke is visible using the above formula (1).

[0034] The calculated opacity of portion A, where the smoke is visible, is output externally by the result output unit 77. The result output unit 77 outputs the opacity calculation result by displaying it on a monitor screen, printing it, or transmitting it to an external communication terminal such as a smartphone or tablet.

[0035] (Effects) In the smoke concentration evaluation device 3A, smoke concentration evaluation system 1A, and smoke concentration evaluation method configured above, information regarding the opacity of image P1 is obtained based on the brightness of pixels in the smoke-containing portion A, which is identified based on the difference between multiple images P1 of the region Z1 including the smoke exhaust unit 100. As a result, the smoke concentration can be evaluated based on the acquired opacity information.

[0036] Furthermore, the image processing unit 72 identifies the pixels in the portion A where smoke is visible by performing frame difference processing between multiple images P1. This makes it possible to easily identify the portion A where smoke is visible by obtaining multiple images P1 from the video of portion A where smoke is visible as it flows moment by moment, when the region Z1 including the smoke exhaust unit 100 is captured in video.

[0037] Furthermore, the luminance acquisition unit 74 corrects the luminance of pixels in image P1 of region Z1, which includes the smoke exhaust unit 100, based on the initial luminance of the initial image when no smoke is being emitted from the smoke exhaust unit 100. By calculating the opacity based on the luminance of the pixels corrected in this way, the influence of fluctuations in the luminance of the background portion of the smoke exhaust unit 100 due to weather conditions, etc., can be suppressed in image P1. As a result, the smoke density can be evaluated with higher accuracy.

[0038] (Second Embodiment) Next, a second embodiment of the smoke concentration evaluation device, smoke concentration evaluation system, smoke concentration evaluation method, and program according to the present disclosure will be described. In the second embodiment described below, components common to the first embodiment are denoted by the same reference numerals in the figures and their descriptions are omitted.

[0039] Figure 8 shows an example of an extracted image extracted from an image in a smoke concentration evaluation device according to the second embodiment of the present disclosure. As shown in Figure 3, in the smoke concentration evaluation device 3B of the smoke concentration evaluation system 1B according to the present embodiment, the image acquisition unit 71 acquires a plurality of images P1 taken at time intervals. As shown in Figure 8, the image processing unit 72 acquires an extracted image P3 by extracting a preset portion of area Z2, including the smoke exhaust unit 100, from each of the acquired plurality of images P1.

[0040] Figure 9 shows an example of an image obtained by frame difference processing using a smoke concentration evaluation device according to the second embodiment of this disclosure. The image processing unit 72 performs grayscale processing on the extracted image P3, and then performs frame difference processing on multiple extracted images P3 to obtain an image P4 as shown in Figure 9, and identifies pixels where a change in scale value, i.e., brightness, has occurred. By identifying pixels where a change in scale value (brightness) has occurred through frame difference processing, the image processing unit 72 identifies the portion of image P4 in which black smoke (smoke) is visible, that is, the portion A in which black smoke exists. Here, it is preferable to set the region Z2 of the extracted image P3 so that smoke from the smoke exhaust unit 100 always covers the entire region Z2. In this case, the identification of the portion A in which black smoke exists by frame difference processing may be omitted.

[0041] The luminance acquisition unit 74 acquires the luminance of multiple pixels that make up the extracted image P3. For each pixel in the extracted image P3, the luminance acquisition unit 74 acquires the scale value, i.e., the luminance, of each pixel in the portion A where the smoke is visible.

[0042] The opacity acquisition unit 75 calculates the opacity of the extracted image P3 as information regarding the opacity of the extracted image P3, based on the luminance of multiple pixels in the portion A where the smoke is visible, that is, the luminance of multiple pixels where a change in scale value (luminance) occurred, for example, using the above formula (1).

[0043] In the smoke evaluation method of this embodiment, in step S12 (see Figure 7) which identifies the pixels of the portion A in which smoke is captured, the image processing unit 72 obtains an extracted image P3 by extracting a predetermined portion of area Z2 from each of the multiple images P1 acquired by the image acquisition unit 71. Subsequently, the image processing unit 72 performs grayscale processing and frame difference processing on the extracted image P3 to identify the portion A (area) in which black smoke is present, as shown in Figure 9.

[0044] In step S13 of acquiring the luminance of pixels in portion A where smoke is captured, a luminance acquisition unit 74 acquires the scale value, that is, the luminance, of the pixels of an extracted image P3 corresponding to portion A where smoke is captured. Further, in step S13, the luminance acquisition unit 74 corrects the detected luminance based on an initial image captured in advance in a state where no smoke is discharged from a smoke discharge unit 100. The luminance acquisition unit 74 corrects the luminance of all pixels of an image P1 based on the initial image captured in a state where no smoke is discharged from the smoke discharge unit 100.

[0045] Thereafter, in step S14 of acquiring information related to image opacity, an opacity acquisition unit 75 acquires information related to the opacity of the extracted image P3 according to the above formula (1) based on the luminance of pixels in portion A where smoke is captured in the extracted image P3.

[0046] (Effects) In the smoke density evaluation device 3B, the smoke density evaluation system 1B, and the smoke density evaluation method having the above configuration, the smoke density can also be effectively evaluated in the same manner as in the above embodiment.

[0047] Further, an extracted image P3 obtained by extracting a partial region Z2 including the smoke discharge unit 100 is acquired from each of the acquired plurality of images P1, and smoke density evaluation is performed targeting the extracted image P3. As described above, by extracting the region Z2 near the smoke discharge unit 100 covered by smoke from the smoke discharge unit 100 as the extracted image P3, it is possible to suppress the influence of the flowing direction of smoke from the smoke discharge unit 100 caused by wind or the like, and stably perform smoke density evaluation.

[0048] (Third Embodiment) Next, a third embodiment of a smoke density evaluation device, a smoke density evaluation system, a smoke density evaluation method, and a program according to the present disclosure will be described. In the third embodiment described below, the same reference numerals are given to configurations common to the above first and second embodiments in the drawings, and description thereof will be omitted.

[0049] Fig. 10 is a diagram showing the configuration of a smoke density evaluation system according to the third embodiment of the present disclosure. As shown in Fig. 10, a smoke density evaluation system 1C includes a camera 2, a luminance reference member 150, and a smoke density evaluation device 3C.

[0050] The luminance reference member 150 is positioned within the area Z1 that can be photographed by the camera 2. The luminance reference member 150 serves as the luminance reference when the luminance acquisition unit 74 acquires luminance. The luminance reference member 150 has, for example, a black portion 152 with a grayscale scale value of 0 and a white portion 151 with a scale value of 255. The luminance reference member 150 may have scale values ​​different from those exemplified here.

[0051] Camera 2 photographs the region Z1, which includes the smoke exhaust unit 100 that discharges smoke. Camera 2 also photographs the brightness reference member 150, which is located within region Z1, together with the smoke exhaust unit 100.

[0052] Figure 11 shows an example of a grayscale image obtained using the smoke density evaluation device according to the third embodiment of this disclosure. When the luminance acquisition unit 74 of the smoke density evaluation device 3C acquires the luminance of a plurality of pixels constituting the image P5 or extracted image P6 as shown in Figure 11, it acquires the luminance of the portion of the luminance reference member 150 that is depicted in the image P5. The luminance acquisition unit 74 corrects the overall luminance of the image P5 or extracted image P6 so that the luminance of the luminance reference member 150 in the image P5 becomes a predetermined luminance (in this embodiment, the scale value of the black portion 152: 0, the scale value of the white portion 151: 255). Based on the corrected luminance, the luminance acquisition unit 74 acquires the scale value, i.e., the luminance, of the pixels in portion A where smoke is depicted.

[0053] (Effects) The smoke concentration evaluation device 3C, smoke concentration evaluation system 1C, and smoke concentration evaluation method configured as described above can effectively evaluate the smoke concentration, similar to the embodiment described above.

[0054] Furthermore, the camera 2 captures a luminance reference member 150 located within the area Z1 that can be photographed by the camera 2, and the luminance acquisition unit 74 detects the luminance of multiple pixels based on the luminance of the luminance reference member 150 captured in the image P5. This allows for stable evaluation of smoke density while suppressing the effects of luminance fluctuations due to changes in weather and sunlight conditions.

[0055] (Fourth Embodiment) Next, a fourth embodiment of the smoke concentration evaluation device, smoke concentration evaluation system, smoke concentration evaluation method, and program according to the present disclosure will be described. In the fourth embodiment described below, components common to the first to third embodiments described above are denoted by the same reference numerals in the figures and their descriptions are omitted.

[0056] Figure 12 shows an example of a grayscale image obtained using the smoke density evaluation device according to the fourth embodiment of the present disclosure. In the smoke density evaluation device 3D of the smoke density evaluation system 1D according to this embodiment, the opacity acquisition unit 75 divides the image P1 acquired by the image acquisition unit 71 into a plurality of divided images Ps. The opacity acquisition unit 75 calculates the opacity for each divided image Ps based on the luminance of the pixels in the portion A where smoke is visible, that is, the luminance of the plurality of pixels where a change in scale value (luminance) occurred, for example, using the above formula (1).

[0057] (Effects) The smoke concentration evaluation device 3D, smoke concentration evaluation system 1D, and smoke concentration evaluation method with the above configuration can effectively evaluate the smoke concentration, similar to the above embodiment.

[0058] Furthermore, by dividing image P1 into multiple segmented images Ps and obtaining information on the opacity of each segmented image Ps, it is possible to understand the distribution of smoke density in the entire region Z1 of image P1. This makes it possible to understand not only the smoke density but also the direction in which the smoke is flowing.

[0059] (Other Embodiments) Although embodiments of the present disclosure have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments and includes design changes and the like that do not depart from the gist of the present disclosure. In the above embodiments, the brightness of pixels in image P1 of region Z1 including the smoke exhaust unit 100 is corrected based on the initial brightness of the initial image when no smoke is being emitted from the smoke exhaust unit 100, and the corrected brightness is obtained, but the present invention is not limited to this. For example, instead of correcting the brightness based on the initial brightness of the initial image when no smoke is being emitted from the smoke exhaust unit 100, the brightness obtained from image P1 acquired by the brightness acquisition unit 74 may be used as is to obtain the opacity. In other words, in image P1, the brightness and opacity of part A in which smoke is visible may be evaluated absolutely rather than relative to the initial brightness of the initial image when no smoke is being emitted. In this case, the smoke from the smoke exhaust unit 100 can be evaluated in a state close to what is seen, regardless of the weather.

[0060] In the above embodiment, the portion containing smoke is identified by performing frame difference processing on two frames of image P1 that are in a temporal order, but the method is not limited to this. For example, the portion A containing smoke may be identified by taking the difference between an initial image of a state in which no smoke is being emitted from the smoke exhaust unit 100 and each image P1.

[0061] In the above embodiment, camera 2 is configured to record video, but it is not limited to this. Camera 2 may also be configured to take still images at predetermined time intervals.

[0062] In the above embodiment, the opacity acquisition unit 75 calculates the opacity using formula (1) based on the brightness of the pixels in part A where the smoke is captured, but it is not limited to this. For example, the opacity acquisition unit 75 may acquire opacity and transmittance as information about opacity from formulas other than formula (1). Also, the opacity acquisition unit 75 may acquire information indicating the opacity in multiple levels from the calculated opacity.

[0063] Furthermore, a program to implement all or part of the functions of the smoke concentration evaluation devices 3A to 3D may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be loaded into a computer system and executed to perform processing by each functional unit. Here, "computer system" includes hardware such as the OS and peripheral devices. Also, if a WWW system is used, "computer system" also includes the homepage provisioning environment (or display environment). Furthermore, "computer-readable recording medium" refers to portable media such as CDs, DVDs, USBs, and storage devices such as hard disks built into the computer system. In addition, if this program is distributed to the smoke concentration evaluation devices 3A to 3D via a communication line, the smoke concentration evaluation devices 3A to 3D that receive the program may unpack it into storage 64 and execute the above processing. Furthermore, the above program may only implement some of the functions described above, and may also be able to implement the above functions in combination with programs already recorded in the computer system.

[0064] <Note> The smoke concentration evaluation devices 3A to 3D, smoke concentration evaluation systems 1A to 1D, smoke concentration evaluation methods, and programs described in each embodiment can be understood, for example, as follows.

[0065] (1) The smoke concentration evaluation apparatus 3A to 3D according to the first embodiment includes an image acquisition unit 71 that acquires a plurality of images of a region Z1 including a smoke exhaust unit 100 that discharges smoke, which are taken at time intervals; an image processing unit 72 that identifies pixels in the portion A in which the smoke is captured from among a plurality of pixels constituting the image P1 based on the difference between the plurality of images; a brightness acquisition unit 74 that acquires the brightness of the pixels in the portion A in which the smoke is captured; and an opacity acquisition unit 75 that acquires information regarding the opacity of the image P1 based on the brightness of the pixels in the portion A in which the smoke is captured.

[0066] These smoke concentration evaluation devices 3A to 3D acquire the brightness of pixels in the smoke-containing portion A based on the difference between multiple images P1 of the region Z1 including the smoke exhaust unit 100, and further acquire information regarding the opacity of image P1. As a result, the smoke concentration can be evaluated based on the acquired opacity information.

[0067] (2) The smoke concentration evaluation apparatus 3A to 3D according to the second embodiment is the smoke concentration evaluation apparatus 3A to 3D of (1), wherein the plurality of images P1 acquired by the image acquisition unit 71 are obtained by dividing a video captured at a predetermined number of frames per unit time into frames, and the image processing unit 72 identifies the pixels of the portion A in which the smoke is captured by performing frame difference processing between the plurality of images P1.

[0068] This allows for easy identification of the portion A showing smoke flowing moment by moment by performing frame difference processing between multiple images P obtained by dividing the video into frames.

[0069] (3) The smoke concentration evaluation devices 3A to 3D according to the third embodiment are the smoke concentration evaluation devices 3A to 3D of (1) or (2), wherein the image acquisition unit 71 acquires an initial image of the region Z1 when no smoke is being emitted from the smoke exhaust unit 100, the brightness acquisition unit 74 acquires corrected brightness by correcting the brightness of the plurality of pixels constituting the image P based on the initial brightness of each of the plurality of pixels constituting the initial image, and the opacity acquisition unit 75 acquires information regarding the opacity of the image P based on the corrected brightness of the plurality of pixels.

[0070] This allows the brightness of pixels in image P1 of region Z1, which includes the smoke exhaust unit 100, to be corrected based on the initial brightness of the initial image when no smoke is being emitted from the smoke exhaust unit 100, and the corrected brightness is obtained. By calculating the opacity of the pixels based on the corrected brightness of the multiple pixels obtained in this way, the influence of weather-related fluctuations on the background portion of the smoke exhaust unit 100 in image P1 can be suppressed. As a result, the smoke density can be evaluated with higher accuracy.

[0071] (4) The smoke concentration evaluation devices 3B, 3C according to the fourth embodiment are any one of the smoke concentration evaluation devices 3B, 3C of (1) to (3), wherein the image acquisition unit 71 acquires an extracted image P3 by extracting a portion of the region Z2 including the smoke exhaust unit 100 from each of the plurality of images P1 acquired by the image acquisition unit 71, the image processing unit 72 identifies the pixels of the portion A in which the smoke is captured in the extracted image P3, and the brightness acquisition unit 74 acquires the brightness of the pixels of the portion A in which the smoke is captured.

[0072] With this configuration, an extracted image P3 is obtained by extracting a portion of the region Z2 including the smoke exhaust unit 100 from each of the multiple images P1 acquired, and the smoke density is evaluated using this extracted image P3. In this way, by extracting the region Z1 near the smoke exhaust unit 100 that is covered by smoke from the smoke exhaust unit 100 as the extracted image P3, the influence of the direction in which smoke flows from the smoke exhaust unit 100 due to wind, etc., is suppressed, and the smoke density can be evaluated stably.

[0073] (5) The smoke concentration evaluation device 3D according to the fifth embodiment is any one of the smoke concentration evaluation devices 3D of (1) to (4), wherein the opacity acquisition unit 75 divides the image P1 into a plurality of divided images Ps and acquires information regarding the opacity of each of the divided divided images Ps.

[0074] With this configuration, image P1 is divided into multiple segmented images Ps, and by obtaining information on the opacity of each of the segmented images Ps, the distribution of smoke density in the entire image P1 can be understood. This makes it possible to understand not only the smoke density but also the direction in which the smoke is flowing.

[0075] (6) The smoke concentration evaluation system 1A to 1D according to the sixth embodiment comprises a camera 2 that photographs a region Z1 including a smoke exhaust section 100 that discharges smoke, and one of the smoke concentration evaluation devices 3A to 3D from (1) to (5).

[0076] With this configuration, the smoke density can be evaluated by obtaining information on the brightness of pixels in the smoke-containing portion A and the opacity of image P based on the difference between multiple images P of the region Z1 including the smoke exhaust unit 100. As a result, the smoke density can be effectively evaluated.

[0077] (7) The smoke density evaluation system 1C according to the seventh embodiment is the smoke density evaluation system 1C of (6), further comprising a luminance reference member 150 which is arranged in the region Z1 that can be photographed by the camera 2 and serves as a reference for the luminance, and the luminance acquisition unit 74 corrects the luminance of a plurality of pixels constituting the image P1 based on the luminance of the luminance reference member 150 captured in the image P1.

[0078] With this configuration, the camera 2 captures a luminance reference member 150 located within the area Z1 that can be photographed, and the luminance acquisition unit 74 detects the luminance of multiple pixels based on the luminance of the luminance reference member 150 captured in the image P. This makes it possible to stably evaluate the smoke density while suppressing the effects of luminance fluctuations due to changes in weather and sunlight conditions.

[0079] (8) A smoke density evaluation method according to the eighth embodiment includes: step S11 of acquiring a plurality of images P1 of a region Z1 including a smoke exhaust unit 100 that discharges smoke, which are taken at time intervals; step S12 of identifying the pixels of the portion A in which the smoke is captured from among a plurality of pixels constituting the image P based on the difference between the plurality of images P; step S13 of acquiring the brightness of the pixels of the portion A in which the smoke is captured; and step S14 of acquiring information regarding the opacity of the image P1 based on the brightness of the pixels of the portion A in which the smoke is captured.

[0080] This allows for the evaluation of smoke density by obtaining the brightness of pixels in the smoke-containing portion A based on the difference between multiple images P1 of the region Z1 including the smoke exhaust unit 100, and by obtaining information regarding the opacity of image P1. As a result, smoke density can be effectively evaluated.

[0081] (9) The program according to the ninth embodiment causes a computer to perform the following steps: S11 to acquire a plurality of images P of a region Z1 including a smoke exhaust unit 100 that emits smoke, which are taken at time intervals; S12 to identify the pixels of the portion A in which the smoke is captured from among a plurality of pixels constituting the image P based on the difference between the plurality of images P; S13 to acquire the brightness of the pixels of the portion A in which the smoke is captured; and S14 to acquire information regarding the opacity of the image P based on the brightness of the pixels of the portion A in which the smoke is captured.

[0082] This allows for the evaluation of smoke density by obtaining the brightness of pixels in the smoke-containing portion A based on the difference between multiple images P1 of the region Z1 including the smoke exhaust unit 100, and by further obtaining information regarding the opacity of image P1. As a result, smoke density can be effectively evaluated.

[0083] According to the smoke concentration evaluation apparatus, smoke concentration evaluation system, smoke concentration evaluation method, and program of this disclosure, the smoke concentration can be effectively evaluated.

[0084] 1A-1D...Smoke density evaluation system 2...Camera 3A-3D...Smoke density evaluation device 61...CPU 62...ROM 63...RAM 64...Storage 65...Communication module 71...Image acquisition unit 72...Image processing unit 74...Brightness acquisition unit 75...Opaqueness acquisition unit 77...Result output unit 100...Smoke exhaust unit 150...Brightness reference member A...Area where smoke is visible P1...Image P2...Image P3...Extracted image P4...Image P5...Image P6...Extracted image Ps...Segmented image

Claims

An image acquisition unit that acquires multiple images of the area including the smoke exhaust section, taken at time intervals, An image processing unit that identifies the pixels in the portion of the image in which the smoke is visible, based on the difference between multiple images, A brightness acquisition unit that acquires the brightness of pixels in the area where the smoke is captured, The system includes an opacity acquisition unit that acquires information regarding the opacity of the image based on the brightness of the pixels in the portion where the smoke is visible. Smoke concentration evaluation device. 　 The multiple images acquired by the image acquisition unit are obtained by dividing a video, which is shot at a predetermined number of frames per unit time, into frames. The image processing unit identifies the pixels in the portion of the image where the smoke is visible by performing frame difference processing between multiple images. The smoke concentration evaluation apparatus according to claim 1. 　 The image acquisition unit acquires an initial image of the region when no smoke is being emitted from the smoke exhaust unit. The brightness acquisition unit acquires corrected brightness by correcting the brightness of the plurality of pixels constituting the image based on the initial brightness of each of the plurality of pixels constituting the initial image. The opacity acquisition unit acquires information regarding the opacity of the image based on the corrected brightness of the plurality of pixels. The smoke concentration evaluation apparatus according to claim 1 or 2. 　 The image acquisition unit acquires an extracted image from each of the multiple images acquired by the image acquisition unit, which is an extracted image of a portion of the region including the smoke exhaust unit that has been set in advance. The image processing unit identifies the pixels in the extracted image that contain the smoke, The luminance acquisition unit acquires the luminance of the pixels in the portion where the smoke is visible. The smoke concentration evaluation apparatus according to claim 1 or 2. 　 The aforementioned opacity acquisition unit is, The aforementioned image is divided into multiple segmented images, and information regarding the opacity of each of the segmented images is obtained. The smoke concentration evaluation apparatus according to claim 1 or 2. 　 A camera that photographs the area including the smoke exhaust section, A smoke concentration evaluation device according to claim 1 or 2, comprising Smoke concentration evaluation system. 　 The system further comprises a luminance reference member, which is positioned within the area that can be photographed by the camera and serves as a reference for the luminance, The luminance acquisition unit corrects the luminance of the plurality of pixels constituting the image, using the luminance of the luminance reference member captured in the image as a reference. The smoke concentration evaluation system according to claim 6. 　 The steps include acquiring multiple images of the region including the smoke exhaust unit, taken at time intervals, A step of identifying the pixels in the portion of the image in which the smoke is visible, based on the difference between multiple images, The steps include obtaining the brightness of the pixels in the area where the smoke is visible, The step includes obtaining information regarding the opacity of the image based on the brightness of the pixels in the portion where the smoke is visible. Method for evaluating smoke concentration. 　 The steps include acquiring multiple images of the region including the smoke exhaust unit, taken at time intervals, A step of identifying the pixels in the portion of the image in which the smoke is visible, based on the difference between multiple images, The steps include obtaining the brightness of the pixels in the area where the smoke is visible, The steps include obtaining information regarding the opacity of the image based on the brightness of the pixels in the portion where the smoke is visible, Make the computer perform a process that includes [this]. program.

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