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

Abstract

Effectively evaluate smoke concentration. [Solution] The smoke density evaluation device comprises: an image acquisition unit that acquires multiple images of a region including a smoke exhaust unit that emits smoke, taken at time intervals; an image processing unit that identifies pixels in the portion of the image in which smoke is captured, based on the difference between the multiple images; a brightness acquisition unit that acquires the brightness of the pixels in the portion of the image in which smoke is captured; and an opacity acquisition unit that acquires 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.

Description

[[Technical Field]]

[0001] The present disclosure relates to a smoke density evaluation apparatus, a smoke density evaluation system, a smoke density evaluation method, and a program. [[Background Art]]

[0002] Patent Literature 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, performs frame differencing on the image, and detects the generation of smoke in the detection region based on moving pixels detected within the detection region. [[Prior Art Document]] [[Patent Document]]

[0003] [[Patent Document 1]] Japanese Unexamined Patent Application Publication No. 2008-46917 [[Summary of the Invention]] [[Problem to be Solved by the Invention]]

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

[0005] The present disclosure has been made to solve the above problem, 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. [[Means for Solving the Problem]]

[0006] To solve the above problems, the smoke concentration evaluation apparatus according to the present disclosure comprises: an image acquisition unit that acquires a plurality of images of a region including a smoke exhaust unit that emits smoke, taken at time intervals; an image processing unit that identifies 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; a brightness acquisition unit that acquires the brightness of the pixels in the portion of the image in which smoke is captured; and an opacity acquisition unit that acquires 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.

[0007] The smoke concentration evaluation system according to this disclosure comprises a camera that photographs an area including a smoke exhaust section that discharges smoke, and a smoke concentration evaluation device 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. [Effects of the Invention]

[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. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows the configuration of the smoke concentration evaluation system according to the first, second, and fourth embodiments of this disclosure. [Figure 2] This figure shows the hardware configuration of a smoke concentration evaluation device according to an embodiment of the present disclosure. [Figure 3] This figure shows the functional configuration of a smoke concentration evaluation device according to an embodiment of the present disclosure. [Figure 4] This figure shows an example of a grayscale image obtained using the smoke concentration evaluation device according to the first embodiment of this disclosure. [Figure 5] This figure shows an example of an image processed by frame difference processing using the smoke concentration evaluation device according to the first embodiment of this disclosure. [Figure 6] This figure shows an example of the calculation result of the opacity obtained by the smoke concentration evaluation device according to the embodiment of this disclosure. [Figure 7] This is a flowchart showing the flow of the smoke concentration evaluation method according to the embodiment of this disclosure. [Figure 8] This figure shows an example of an extracted image obtained from an image in a smoke concentration evaluation device according to the second embodiment of this disclosure. [Figure 9] This figure shows an example of an image processed by frame difference processing using the smoke concentration evaluation device according to the second embodiment of this disclosure. [Figure 10] This figure shows the configuration of the smoke concentration evaluation system according to the third embodiment of this disclosure. [Figure 11] This figure shows an example of a grayscale image obtained using the smoke concentration evaluation device according to the third embodiment of this disclosure. [Figure 12] This figure shows an example of a grayscale image obtained using the smoke concentration evaluation device according to the fourth embodiment of this disclosure. [Modes for carrying out the invention]

[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 Smoke Density Evaluation System) As shown in FIG. 1, the smoke density evaluation system 1A includes a camera 2 and a smoke density evaluation device 3A. Here, the smoke density evaluation system 1A evaluates the density of smoke discharged from a smoke discharge unit 100. The smoke discharge unit 100 is, for example, a stack 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, a hospital, a factory, or the like.

[0014] (Camera) The camera 2 photographs an area Z1 including the smoke discharge unit 100 that discharges smoke. The camera 2 is installed at a position where the area Z1 including the smoke discharge unit 100 can be photographed, such as on the roof of a building where the smoke discharge unit 100 is installed. It is preferable that the camera 2 is fixed via an appropriate stay or the like so as to suppress positional displacement caused by wind, vibration, or the like.

[0015] In the present embodiment, the camera 2 captures a moving image of the area Z1 including the smoke discharge unit 100. In the present embodiment, the camera 2 captures a moving image at a preset number of frames per unit time. The camera 2 transmits the captured moving image data to the smoke density 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) FIG. 2 is a diagram showing the hardware configuration of the smoke density evaluation device according to an embodiment of the present disclosure. As shown in FIG. 2, the smoke density evaluation device 3A is a computer including pieces of hardware such as a CPU 61, a ROM 62, a RAM 63, a storage 64 such as an HDD (Hard Disk Drive), and a communication module 65.

[0017] (Functional Block Diagram) FIG. 3 is a diagram showing the functional configuration of the smoke density evaluation device according to an embodiment of the present disclosure. The smoke concentration evaluation device 3A evaluates the smoke concentration from the smoke exhaust unit 100 based on multiple images transmitted from the camera 2, by having the CPU 61 execute a program that is pre-stored in the device. 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 applies a grayscale conversion process to 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 shows an example of an image processed by frame difference processing using the smoke concentration evaluation device according to the embodiment of this disclosure. In this embodiment, the image processing unit 72 uses frame difference processing to identify (extract) pixels that have changed between the scale value of each pixel constituting image P1 of one frame and the scale value of each pixel constituting image P1 of the frame immediately preceding that frame, as shown in Figure 5. In other words, the image processing unit 72 identifies pixels in which a change in scale value, i.e., brightness, has occurred between two images P1 taken at different time intervals. In Figure 5, pixels in which a change in brightness has occurred are shown in white, and pixels in which no change in brightness has occurred are shown in black. If black smoke is present in image P2 obtained by frame difference processing, 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 in which 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 smoke-containing area A 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 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 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 and average values ​​of the scale values ​​of the pixels in the background area, and use the calculated median and average values ​​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 part A where 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, noise may be generated in pixels where there is no change in scale value or the change in scale value is small. In contrast, noise can be reduced by converting the scale values ​​of multiple pixels to the average value, so-called averaging processing.

[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 process known as minimization.

[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).

number

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

[0028] (Procedure for evaluating smoke concentration) Figure 7 is a flowchart showing the flow of the smoke concentration evaluation method according to the embodiment of this disclosure. As shown in Figure 7, the smoke density evaluation method according to the embodiment of this 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 the 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 performed repeatedly at predetermined intervals while the smoke concentration evaluation system 1A is operating based on a preset program. Alternatively, the smoke concentration evaluation method in this embodiment may be performed only when the combustion device (not shown) that discharges exhaust gas from the exhaust section 100 is starting up, when it is more 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 for 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, the image processing unit 72 first 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 of the portion A in which smoke is visible based on image P2 obtained by performing difference processing on multiple grayscale images P1. In this embodiment, the image processing unit 72 performs frame difference processing 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 portion A (range) in which black smoke is present.

[0031] 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 pixels in part A where smoke is visible in the grayscaled 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 scale value of multiple pixels in part A where smoke is present, and convert the brightness of the pixels in part A where smoke is present to the calculated average or minimum value.

[0033] In step S14, which involves acquiring information about the opacity of image P, the opacity acquisition unit 75 acquires information about 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 and Benefits) In the smoke concentration evaluation device 3A, smoke concentration evaluation system 1A, and smoke concentration evaluation method configured as described 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 area A where smoke is visible by performing frame difference processing between multiple images P1. This makes it easy to identify the area A where smoke is visible by obtaining multiple images P1 from the video of the area A where smoke is visible as it flows moment by moment, when the area 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 this 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 the smoke concentration evaluation apparatus according to the second embodiment of this disclosure. As shown in Figure 3, in the smoke concentration evaluation device 3B of the smoke concentration evaluation system 1B according to this 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 processed by frame difference processing using the 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 part of image P4 where black smoke (smoke) is visible, that is, the part A where black smoke exists. Here, it is preferable to set the region Z2 of the extracted image P3 so that the smoke from the smoke exhaust unit 100 always covers the entire region Z2. In this case, the identification of the part A where 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, specifically in the portion A where the smoke is visible, the luminance acquisition unit 74 acquires the scale value, i.e., the luminance of each pixel.

[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 part A where the smoke is visible, that is, the luminance of multiple pixels where a change in scale value (luminance) occurred, for example using equation (1) above.

[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 region Z2 from each of the multiple images P1 acquired by the image acquisition unit 71. Subsequently, the image processing unit 72 performs grayscale conversion and frame difference processing on the extracted image P3 to identify the area A (range) where black smoke is present, as shown in Figure 9.

[0044] 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 the extracted image P3 that correspond to part A where smoke is visible. Furthermore, in step S13, the brightness acquisition unit 74 corrects the detected brightness based on an initial image previously captured in a state where no smoke is being emitted from the smoke exhaust unit 100. The brightness acquisition unit 74 corrects the brightness of all pixels in image P1 based on the initial image in a state where no smoke is being emitted from the smoke exhaust unit 100.

[0045] Subsequently, in step S14, which involves acquiring information on the opacity of the image, the opacity acquisition unit 75 acquires information on the opacity of the extracted image P3 based on the brightness of the pixels in part A where smoke is visible, using the above equation (1).

[0046] (Effects and Benefits) In the smoke concentration evaluation device 3B, smoke concentration evaluation system 1B, and smoke concentration evaluation method configured as described above, the smoke concentration can be effectively evaluated in the same manner as in the above embodiment.

[0047] Furthermore, an extracted image P3 is obtained by extracting a portion of region Z2, including the smoke exhaust unit 100, from each of the multiple images P1 acquired, and the smoke concentration is evaluated using this extracted image P3. In this way, by extracting the region Z2 near the smoke exhaust unit 100, which 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 evaluation of the smoke concentration can be performed stably.

[0048] (Third embodiment) Next, a third embodiment of the smoke concentration evaluation device, smoke concentration evaluation system, smoke concentration evaluation method, and program according to this disclosure will be described. In the third embodiment described below, components common to the first and second embodiments described above are denoted by the same reference numerals in the figures and their descriptions are omitted.

[0049] Figure 10 shows the configuration of a smoke concentration evaluation system according to the third embodiment of this disclosure. As shown in Figure 10, the smoke concentration evaluation system 1C comprises a camera 2, a brightness reference member 150, and a smoke concentration 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 luminance reference member 150 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 concentration evaluation device according to the third embodiment of this disclosure. The luminance acquisition unit 74 of the smoke density evaluation device 3C acquires the luminance of a portion of the luminance reference member 150 that is captured in image P5 when acquiring the luminance of a plurality of pixels that make up image P5 or extracted image P6 as shown in Figure 11. The luminance acquisition unit 74 corrects the overall luminance of image P5 or extracted image P6 so that the luminance of the luminance reference member 150 in 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 captured.

[0053] (Effects and Benefits) 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 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 apparatus, smoke concentration evaluation system, smoke concentration evaluation method, and program according to this 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 concentration evaluation device according to the fourth embodiment of this disclosure. In the smoke concentration evaluation device 3D of the smoke concentration 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 (Figure 12). The opacity acquisition unit 75 calculates the opacity for each divided image Ps based on the luminance of the pixels in the part A where the 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 and Benefits) In the smoke concentration evaluation apparatus 3D, smoke concentration evaluation system 1D, and smoke concentration evaluation method configured as described above, the smoke concentration can be effectively evaluated in the same manner as in 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 this disclosure have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments and may include design changes and the like that do not depart from the gist of this disclosure. In the above embodiment, 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. However, the embodiment 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 the image P1 acquired by the brightness acquisition unit 74 may be used as is to acquire the opacity. In other words, in image P1, the brightness and opacity of the part A in which smoke is visible may be evaluated absolutely rather than relatively with respect to the initial brightness of the initial image when no smoke is being emitted. In this case, regardless of the weather, the smoke from the exhaust unit 100 can be evaluated in a state that closely resembles what is actually seen.

[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 embodiment is not limited to this. For example, the portion A containing smoke may be identified by taking the difference between an initial image in a state where 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 equation (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 regarding opacity from formulas other than formula (1). Furthermore, the opacity acquisition unit 75 may acquire information indicating the opacity at 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 portion A in which smoke is captured from 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 portion A in which 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 portion A in which 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. This allows for the evaluation of smoke concentration based on the acquired opacity information. As a result, the smoke concentration can be effectively evaluated.

[0067] (2) The smoke density evaluation apparatus 3A to 3D according to the second embodiment is the smoke density 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 containing the smoke that is constantly flowing, by performing frame difference processing between multiple images P obtained by dividing the video into frames.

[0069] (3) The smoke concentration evaluation apparatus 3A to 3D according to the third embodiment is the smoke concentration evaluation apparatus 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 and 3C according to the fourth embodiment are any one of the smoke concentration evaluation devices 3B and 3C described in (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 region Z2, including the smoke exhaust unit 100, from each of the multiple images P1 acquired, and the smoke concentration 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 concentration 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 on 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 segmented image 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 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 with reference to 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 emits 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 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 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. [Explanation of symbols]

[0083] 1A~1D...Smoke concentration evaluation system 2…Camera 3A~3D...Smoke concentration 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...Opacity acquisition section 77...Result output section 100...Smoke exhaust section 150... Luminance reference component A... The part where the smoke is visible P1...Image P2...Image P3... Extracted image P4...Image P5...Image P6... Extracted image Ps... Split image

Claims

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

9. 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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