Method and device for calculating optical characteristics of tail flame target

Abstract

The invention provides a method and a device for calculating optical characteristics of a tail flame target. The method comprises the following steps: acquiring detection parameters of a detection camera and a plurality of frames of detection images of a tail flame target; for the plurality of frames of detection images, determining a frame of image where the center position of the tail flame target is located by using a frame difference method, and determining the frame of image as a tail flame target image; determining a pixel region of the tail flame target in the tail flame target image based on the gradient change characteristic of the tail flame target along the central position; and calculating the optical intensity of the tail flame target according to the detection parameters, the pixel area of the tail flame target, the distance between the tail flame target and the detection camera, the calibration coefficient slope and the transmittance. According to the scheme, on the basis that all pixels in the tail flame target image are not calculated, only feature statistics of the tail flame target is carried out, boundary division of the tail flame target is more reasonable, statistics is more comprehensive, and finally, the optical characteristics of the tail flame target in the pixel area can be rapidly and accurately calculated and obtained by combining parameters such as detection parameters and the like.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of automatic image segmentation and processing, and in particular to a method and device for calculating the optical characteristics of a tail flame target. Background Art

[0002] The tail flame target is a coupled multi-physical field of combustion, flow, etc., which is different from the typical solid target. Since the field intensity distribution gradually distributes from the intensity center point to the background gradient, there is no strict boundary, and there is also a certain diffusion effect for the observation camera. Therefore, it is difficult to segment the tail flame target from the background and calculate its characteristics.

[0003] At present, the tail flame target image segmentation technology mainly adopts the threshold segmentation method, which often reduces the tail flame target range because the tail flame target has a large diffusion area. Although the intensity of this area is small, its area accounts for a large proportion and cannot be ignored.

[0004] Therefore, there is an urgent need to provide a method and device for calculating the optical characteristics of a tail flame target. Summary of the invention

[0005] In order to solve the problem that the conventional tail flame target image segmentation method has unreasonable segmentation, resulting in poor calculation accuracy of its optical characteristics, the embodiment of the present invention provides a method and device for calculating the optical characteristics of a tail flame target.

[0006] In a first aspect, an embodiment of the present invention provides a method for calculating the optical characteristics of a tail flame target, the method comprising:

[0007] Obtain detection parameters of the detection camera and several frames of detection images of the tail flame target;

[0008] For the plurality of detection image frames, a frame image where the center position of the tail flame target is located is determined by using a frame difference method, and the frame image is determined as the tail flame target image;

[0009] Determining a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position;

[0010] The optical intensity of the tail flame target is calculated according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope and transmittance of the calibration coefficient.

[0011] In a second aspect, an embodiment of the present invention further provides an optical characteristic calculation device for a tail flame target, the device comprising:

[0012] An acquisition unit, used to acquire detection parameters of the detection camera and several frames of detection images of the tail flame target;

[0013] A first determining unit is used to determine a frame of image where the center position of the tail flame target is located by using a frame difference method for the plurality of frames of detection images, and determine the frame of image as the tail flame target image;

[0014] A second determining unit is used to determine a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position;

[0015] A calculation unit is used to calculate the optical intensity of the tail flame target according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope of the calibration coefficient and the transmittance.

[0016] In a third aspect, an embodiment of the present invention further provides a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, enables the computer to execute the method described in any embodiment of this specification.

[0018] On the other hand, an embodiment of the present application further provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes any of the methods described in the above embodiments.

[0019] The embodiment of the present invention provides a method and device for calculating the optical characteristics of a tail flame target. First, for the detection images of several frames of the tail flame target obtained, a frame difference method is used to determine the tail flame target image and the approximate center position of the tail flame target. Then, the gradient change characteristics of the distribution intensity of the tail flame target, that is, "gradually spreading from the center position of the tail flame target to the surrounding area until it is indistinguishable from the background", are combined to determine the pixel area of ​​the tail flame target in the tail flame target image. In this way, without calculating all the pixels in the tail flame target image, only the characteristic statistics of the tail flame target itself are performed, and the boundary division of the tail flame target is more reasonable and the statistics are more comprehensive. Finally, the optical characteristics of the tail flame target in the pixel area can be quickly and accurately calculated in combination with detection parameters and other parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a flow chart of a method for calculating the optical characteristics of a tail flame target provided by one embodiment of the present invention;

[0022] Figure 2 is a schematic diagram of a pixel expansion area of ​​a tail flame target provided by an embodiment of the present invention;

[0023] Figure 3 is a schematic diagram of a tail flame target image provided by an embodiment of the present invention;

[0024] Figure 4 is a hardware architecture diagram of a computing device provided by an embodiment of the present invention;

[0025] Figure 5 It is a structural diagram of an optical characteristic calculation device for a tail flame target provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] The specific implementation of the above concept is described below.

[0028] Please refer to Figure 1 The embodiment of the present invention provides a method for calculating the optical characteristics of a tail flame target, the method comprising:

[0029] Step 100, acquiring detection parameters of a detection camera and several frames of detection images of the tail flame target;

[0030] Step 102, for the plurality of detection image frames, a frame image where the center position of the tail flame target is located is determined by using a frame difference method, and the frame image is determined as the tail flame target image;

[0031] Step 104, determining a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position;

[0032] Step 106, calculating the optical intensity of the tail flame target according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope of the calibration coefficient and the transmittance.

[0033] In an embodiment of the present invention, firstly, for the detection images of the tail flame target of several frames obtained, the frame difference method is used to determine the tail flame target image and the approximate center position of the tail flame target. Then, the gradient change characteristics of the distribution intensity of the tail flame target, that is, "gradually spreading from the center position of the tail flame target to the surroundings until it is indistinguishable from the background", are combined to determine the pixel area of ​​the tail flame target in the tail flame target image. In this way, without calculating all the pixels in the tail flame target image, only the feature statistics of the tail flame target itself are performed, and the boundary division of the tail flame target is more reasonable and the statistics are more comprehensive. Finally, the optical characteristics of the tail flame target in the pixel area can be quickly and accurately calculated in combination with detection parameters and other parameters.

[0034] For step 100:

[0035] In the embodiment of the present invention, if the image of the tail flame target obtained is a grayscale image, no unified processing is required. If the several frames of detection images of the tail flame target obtained are RGB format images, the RGB three-channel results of each pixel in each frame of the image need to be converted into a grayscale (GRAY) single-channel result. Among them, the conversion relationship between the GRAY single channel and the RGB three-channel can be converted using the following formula: GRAY = 0.2989 × R + 0.5870 × G + 0.1140 × B; in this way, the image values ​​of each frame of the image can be uniformly compared.

[0036] Regarding step 102:

[0037] In some implementations, step 102 includes:

[0038] Subtract the pixel values ​​of each pixel point in each of two adjacent detection image frames to obtain a plurality of groups of pixel difference values; wherein each group of pixel difference values ​​includes a plurality of pixel point difference values;

[0039] A group of maximum pixel differences is selected from the plurality of groups of pixel differences, and the pixel point corresponding to the maximum pixel point difference in the group of pixel differences is determined as the center position of the tail flame target, and the frame image corresponding to the pixel point is further determined as the tail flame target image.

[0040] In the embodiment of the present invention, considering that in the detection image of the tail flame target, the image background information is relatively fixed, while the intensity and position information of the tail flame target are unstable, the frame difference method is used according to the characteristic distribution law of the tail flame target to achieve effective extraction of the position information of the tail flame target.

[0041] Specifically, assuming that there are N frames of detection images of the tail flame target, the i-th frame detection image can be represented as FRAME{i}(row,col), wherein row and col represent the row pixel value and column pixel value of the image, respectively, that is, the grayscale value of each pixel point after being acquired or converted in step 100.

[0042] Subtract the i-th frame image from the i-1-th frame image, that is, the pixel difference of the i-th frame can be expressed as Difframe{i}(row,col):

[0043] Difframe{i}(row,col)=FRAME{i}(row,col)-FRAME{i-1}(row,col)

[0044] Select a group of pixel differences Difframe{i}(row,col) with the largest difference, and further determine the location of the maximum value in Difframe{i}(row,col), so as to determine the approximate center position of the tail flame target, which can be expressed as follows:

[0045] [row,col]=find(Difframe{i}(row,col)==max(Difframe{i}(row,col)))

[0046] In the formula, the max function is to find the maximum value in Difframe{i}(row,col), and the find function is to find the row pixels and column pixels equal to the maximum value. The image where the pixel is located is the tail flame target image.

[0047] It should be noted that since the tail flame target contains many pixels and saturation may occur, the maximum value will inevitably appear more than once in the tail flame target image. However, all maximum values ​​are included in the tail flame. Therefore, you can select the row pixel number and column pixel number where any maximum value appears. For example, you can select row(1) and col(1).

[0048] Regarding step 104:

[0049] In some embodiments, before determining the pixel area of ​​the tail flame target in the tail flame target image based on the gradient change characteristics of the tail flame target along the center position, it also includes: judging whether the center position of the tail flame target is located at the boundary line of the tail flame target image.

[0050] Since the intensity value of the core area of ​​the tail flame target is larger and the intensity value of the peripheral area is smaller, and it presents a certain gradient distribution pattern, in the embodiment of the present invention, the image is gradually expanded and judged outward from the center position determined in step 102 as the starting point, so as to determine the pixel area of ​​the tail flame target in the tail flame target image.

[0051] At the same time, in order to accurately determine the tail flame target pixel area, when the center position determined in step 102 is located at a different position in the tail flame target image, the processing method is different, as follows:

[0052] If the center position is within the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner:

[0053] Step S1: taking the central position as the central point of the pixel expansion area, and sequentially expanding pixels outwards along the four sides of the central point to obtain a pixel expansion area; wherein the pixel expansion area is a square;

[0054] Step S2: Calculate the average gradient value of the central pixel in the pixel expansion area, and determine whether the average gradient value is greater than a first preset threshold;

[0055] Step S3: If yes, the central pixel point is determined as the tail flame target pixel, and the eight pixel points around the central pixel point are respectively used as the center points of the next pixel expansion area, and the execution of steps S1 to S2 is jumped until the calculated average gradient value is less than the first preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

[0056] In the embodiment of the present invention, since the image pixels are square, if the maximum value (i.e., the center position determined in step 102) is not at the boundary, the maximum value pixel [row(i), col(j)] can be taken as the center point, and the pixel expansion area can be obtained by expanding the pixel area around the center point to 8 adjacent pixels (e.g., Figure 2 The center point and its eight adjacent pixels are arranged as shown in Table 1.

[0057] Table 1

[0058] center [row(i),col(j)] Top left [row(i-1),col(j-1)] Right up [row(i-1),col(j)] Top right [row(i-1),col(j+1)] Right [row(i),col(j+1)] Bottom right [row(i+1),col(j+1)] Directly below [row(i+1),col(j)] Lower left [row(i+1),col(j-1)] Right left [row(i),col(j-1)]

[0059] The average gradient value of the center pixel is calculated by the following formula: grad{GRAY(row(i),col(j))}=Average[GRAY(row(i),col(j))-GRAY(row(i+a),col(j+b))]

[0060] In the formula, a and b are the permutations and combinations of +1, 0, and -1 respectively, and a and b cannot be 0 at the same time. The average function is the function for finding the average value;

[0061] When the average gradient value grad{GRAY(row(i),col(j))} of the central pixel is greater than the first preset threshold (i.e., a specific small multiple ε of the central pixel GRAY(row(i),col(j))), the central pixel is determined to be a pixel of the tail flame target, that is:

[0062] grad{GRAY(row(i),col(j))}>εGRAY(row(i),col(j))

[0063] At this time, the pixel value GRAY(row(i),col(j)) of the central pixel is stored in the PLUME array. Then, the eight pixel points around the central point are stored in the CHECK array, and the eight pixel points around the central point are respectively used as the center point of the next pixel expansion area. The above pixel expansion and tail flame target judgment steps are repeated until the calculated average gradient value does not meet the judgment condition of the tail flame target pixel. At this time, the boundary point between the pixel area of ​​the tail flame target and the background area can be determined, so as to achieve a reasonable and accurate division of the tail flame target pixel area.

[0064] It should be noted that when the pixel target in the CHECK array is still the tail flame target, it is necessary to determine whether the expanded 8 pixels are already included in PLUME during expansion. If included, the pixel will not be counted repeatedly.

[0065] In some implementations, if the center position is located on the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner:

[0066] Step A1: taking the center position as the corner point of the pixel expansion area, in the tail flame target image area, sequentially expanding pixels outward along the periphery of the boundary point to obtain a pixel expansion area; wherein the pixel expansion area is a square;

[0067] Step A2: calculating the average gradient value of the corner pixel points in the pixel expansion area, and determining whether the average gradient value is greater than a first preset threshold;

[0068] Step A3: If yes, the corner pixel is determined as the tail flame target pixel, and the three pixels around the corner pixel are respectively used as the corner points of the next pixel expansion area, and the execution of steps A1 to A2 is jumped until the calculated average gradient value is less than the preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

[0069] In the embodiment of the present invention, it is assumed that the maximum value of the number of row pixels of the tail flame target image is n, and the maximum value of the number of column pixels is m. For the case where the maximum value (i.e., the center position determined in step 102) appears at the boundary (including horizontal, vertical, or angular boundaries) of the tail flame target image, it is necessary to determine whether the row pixels or column pixels at the center position are equal to 0 or n(m). If they are equal, it is determined to be a boundary case. At this time, the content outside the boundary is not calculated. Only within the tail flame target image, the center position is used as the corner point of the square expansion area (i.e., one corner point of the square) to expand 3 pixels into the image to obtain an expansion area. At this time, the obtained expansion area is a square containing 4 pixels.

[0070] The average gradient value of the boundary pixels is calculated by the following formula: grad{GRAY(row(i),col(j))}=Average[GRAY(row(i),col(j))-GRAY(row(i+a),col(j+b))]

[0071] In the formula, a and b are the permutations of +1 and 0 respectively, and a and b cannot be 0 at the same time. The average function is the function for finding the average value.

[0072] When the average gradient value grad{GRAY(row(i),col(j))} of the center pixel is greater than the second preset threshold value (i.e., a specific small multiple ε of the center pixel GRAY(row(i),col(j))), the center pixel is determined to be a pixel of the tail flame target. At this time, the pixel value GRAY(row(i),col(j)) of the corner pixel is stored in the PLUME array, and then the three adjacent pixels around the corner are stored in the CHECK array, and the three pixels around the corner are respectively used as the corner points of the next pixel expansion area, and the above pixel expansion and tail flame target judgment steps are repeated until the calculated average gradient value does not meet the judgment condition of the tail flame target pixel. At this time, the boundary point between the pixel area of ​​the tail flame target and the background area can be determined, and a reasonable and accurate division of the tail flame target pixel area can be achieved.

[0073] In some implementations, after determining the pixel area of ​​the tail flame target, the method further includes:

[0074] Calculating a pixel average of the tail flame target image, and determining a second preset threshold based on the pixel average;

[0075] The pixel value of each pixel point outside the pixel area of ​​the tail flame target is compared with the second preset threshold value; if there is a pixel point whose pixel value is greater than the second preset threshold value, the pixel point is determined as the tail flame target pixel.

[0076] Considering that when the center position is determined in step 102, the maximum value position may not change and is oversaturated, and the pixels near the oversaturated target pixel are also oversaturated, then the gradient values ​​of these pixels are all 0, such as Figure 3 As shown, it may be misjudged as a background area. Therefore, in the embodiment of the present invention, after the pixel area of ​​the tail flame target is determined, the background area is further restricted.

[0077] Specifically, the pixel average value AverFrame of the entire tail flame target image is calculated by taking advantage of the fact that the value of the oversaturated pixel is significantly greater than the value of the background pixel, that is:

[0078] AverFrame=Average(GRAY(row(i),col(j))),i=1,2,...,n,j=1,2,...,m

[0079] Therefore, the second preset threshold can be determined as: β×AverFrame

[0080] Afterwards, for each pixel value outside the pixel area of ​​the tail flame target (i.e., the background area), if there is a pixel value of a pixel point greater than a second preset threshold, that is:

[0081] GRAY(row(i),col(j))>β×AverFrame

[0082] The pixel point is further determined as the tail flame target pixel, which can further ensure the accuracy of the tail flame target pixel area division, thereby significantly improving the accuracy of tail flame target image extraction and processing while taking into account the computational efficiency.

[0083] Regarding step 106:

[0084] In some embodiments, the optical intensity of the pixel area of ​​the tail flame target is calculated by the following formula:

[0085]

[0086] Wherein, RADIATION is the optical intensity of the pixel area of ​​the tail flame target, k is the slope of the calibration coefficient between grayscale and intensity, GRAYSUM is the accumulated grayscale value of the pixel area of ​​the tail flame target, GRAYBACKGROUND is the background grayscale value, L is the distance between the tail flame target and the detection camera, FOVV is the detection angle of view of the detection camera in the vertical direction, and FOVH is the detection angle of view of the detection camera in the horizontal direction.

[0087] In some embodiments, the grayscale value accumulation GRAYSUM of the pixel area of ​​the tail flame target is calculated by the following formula:

[0088]

[0089] Wherein, N is the number of pixels in the pixel area of ​​the tail flame target.

[0090] In the embodiment of the present invention, after the pixel area of ​​the tail flame target is accurately divided in step 104, the optical characteristic information of the tail flame target image can be accurately calculated according to the detection parameters of the camera, the calibration coefficient slope k between grayscale and intensity, the transmittance trans and other information.

[0091] like Figure 4 , Figure 5 As shown, an embodiment of the present invention provides an optical characteristic calculation device for a tail flame target. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Figure 4 FIG. 1 is a hardware architecture diagram of a computing device where an optical characteristic computing device of a tail flame target provided by an embodiment of the present invention is located, except Figure 5 In addition to the processor, memory, network interface, and non-volatile memory shown in the figure, the computing device in which the device is located in the embodiment may also generally include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 5 As shown, as a device in a logical sense, the CPU of the computing device in which it is located reads the corresponding computer program in the non-volatile memory into the memory and runs it. This embodiment provides an optical characteristic calculation device for a tail flame target, and the device includes:

[0092] An acquisition unit 501 is used to acquire detection parameters of a detection camera and several frames of detection images of a tail flame target;

[0093] A first determining unit 502 is used to determine a frame of image where the center position of the tail flame target is located by using a frame difference method for the plurality of frames of detection images, and determine the frame of image as the tail flame target image;

[0094] A second determining unit 503 is used to determine a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position;

[0095] The calculation unit 504 is used to calculate the optical intensity of the tail flame target according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope of the calibration coefficient and the transmittance.

[0096] In an embodiment of the present invention, the acquisition unit 501 can be used to execute step 100 in the above method embodiment, the first determination unit 502 can be used to execute step 102 in the above method embodiment, the second determination unit 503 can be used to execute step 104 in the above method embodiment, and the calculation unit 504 can be used to execute step 106 in the above method embodiment.

[0097] In one embodiment of the present invention, when the first determining unit 502 determines a frame of image where the center position of the tail flame target is located by using the frame difference method, the first determining unit 502 includes:

[0098] Subtract the pixel values ​​of each pixel point in each of two adjacent detection image frames to obtain a plurality of groups of pixel difference values; wherein each group of pixel difference values ​​includes a plurality of pixel point difference values;

[0099] A group of maximum pixel differences is selected from the plurality of groups of pixel differences, and the pixel point corresponding to the maximum pixel point difference in the group of pixel differences is determined as the center position of the tail flame target, and the frame image corresponding to the pixel point is further determined as the tail flame target image.

[0100] In one embodiment of the present invention, in the second determination unit 503, before determining the pixel area of ​​the tail flame target in the tail flame target image based on the gradient change characteristics of the tail flame target along the center position, it also includes: judging whether the center position of the tail flame target is located at the boundary line of the tail flame target image.

[0101] In one embodiment of the present invention, in the second determining unit 503, if the center position is within the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner:

[0102] Step S1: taking the central position as the central point of the pixel expansion area, and sequentially expanding pixels outwards along the four sides of the central point to obtain a pixel expansion area; wherein the pixel expansion area is a square;

[0103] Step S2: Calculate the average gradient value of the central pixel in the pixel expansion area, and determine whether the average gradient value is greater than a first preset threshold;

[0104] Step S3: If yes, the central pixel point is determined as the tail flame target pixel, and the eight pixel points around the central pixel point are respectively used as the center points of the next pixel expansion area, and the execution of steps S1 to S2 is jumped until the calculated average gradient value is less than the first preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

[0105] In one embodiment of the present invention, in the second determining unit 503, if the center position is located on the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner:

[0106] Step A1: taking the center position as the corner point of the pixel expansion area, in the tail flame target image area, sequentially expanding pixels outward along the periphery of the boundary point to obtain a pixel expansion area; wherein the pixel expansion area is a square;

[0107] Step A2: calculating the average gradient value of the corner pixel points in the pixel expansion area, and determining whether the average gradient value is greater than a first preset threshold;

[0108] Step A3: If yes, the corner pixel is determined as the tail flame target pixel, and the three pixels around the corner pixel are respectively used as the corner points of the next pixel expansion area, and the execution of steps A1 to A2 is jumped until the calculated average gradient value is less than the first preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

[0109] In one embodiment of the present invention, after determining the pixel area of ​​the tail flame target, the second determining unit 503 further includes:

[0110] Calculating a pixel average of the tail flame target image, and determining a second preset threshold based on the pixel average;

[0111] The pixel value of each pixel point outside the pixel area of ​​the tail flame target is compared with the second preset threshold value; if there is a pixel point whose pixel value is greater than the second preset threshold value, the pixel point is determined as the tail flame target pixel.

[0112] In one embodiment of the present invention, the optical intensity of the pixel area of ​​the tail flame target is calculated by the following formula:

[0113]

[0114] Wherein, RADIATION is the optical intensity of the pixel area of ​​the tail flame target, k is the slope of the calibration coefficient between grayscale and intensity, GRAYSUM is the accumulated grayscale value of the pixel area of ​​the tail flame target, GRAYBACKGROUND is the background grayscale value, L is the distance between the tail flame target and the detection camera, FOVV is the detection angle of view of the detection camera in the vertical direction, and FOVH is the detection angle of view of the detection camera in the horizontal direction.

[0115] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the optical characteristic calculation device for a tail flame target. In other embodiments of the present invention, the optical characteristic calculation device for a tail flame target may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0116] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0117] An embodiment of the present invention further provides a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a method for calculating the optical characteristics of a tail flame target in any embodiment of the present invention is implemented.

[0118] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a method for calculating the optical characteristics of a tail flame target in any embodiment of the present invention.

[0119] Specifically, a system or device equipped with a storage medium can be provided, on which software program code that implements the functions of any of the above-mentioned embodiments is stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program code stored in the storage medium.

[0120] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0121] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.

[0122] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0123] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0124] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement a method for calculating the optical characteristics of a tail flame target provided by the above-mentioned method embodiments.

[0125] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0126] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the optical characteristics of a tail flame target, characterized in that: include: Obtain detection parameters of the detection camera and several frames of detection images of the tail flame target; For the plurality of detection image frames, a frame image where the center position of the tail flame target is located is determined by using a frame difference method, and the frame image is determined as the tail flame target image; Determining a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position; The optical intensity of the tail flame target is calculated according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope and transmittance of the calibration coefficient.

2. The method according to claim 1, characterized in that The method of determining a frame of image where the center position of the tail flame target is located by using the frame difference method includes: Subtract the pixel values ​​of each pixel point in each of two adjacent detection image frames to obtain a plurality of groups of pixel difference values; wherein each group of pixel difference values ​​includes a plurality of pixel point difference values; A group of maximum pixel differences is selected from the plurality of groups of pixel differences, and the pixel point corresponding to the maximum pixel point difference in the group of pixel differences is determined as the center position of the tail flame target, and the frame image corresponding to the pixel point is further determined as the tail flame target image.

3. The method according to claim 1, characterized in that Before determining the pixel area of ​​the tail flame target in the tail flame target image based on the gradient change characteristics of the tail flame target along the center position, the method further includes: judging whether the center position of the tail flame target is located at the boundary line of the tail flame target image.

4. The method according to claim 3, characterized in that If the center position is within the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner: Step S1: taking the central position as the central point of the pixel expansion area, and sequentially expanding pixels outwards along the four sides of the central point to obtain a pixel expansion area; wherein the pixel expansion area is a square; Step S2: Calculate the average gradient value of the central pixel in the pixel expansion area, and determine whether the average gradient value is greater than a first preset threshold; Step S3: If yes, the central pixel point is determined as the tail flame target pixel, and the eight pixel points around the central pixel point are respectively used as the center points of the next pixel expansion area, and the execution of steps S1 to S2 is jumped until the calculated average gradient value is less than the first preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

5. The method according to claim 3, characterized in that: If the center position is located on the boundary line of the tail flame target image, the pixel area of ​​the tail flame target in the tail flame target image is determined in the following manner: Step A1: taking the center position as the corner point of the pixel expansion area, in the tail flame target image area, sequentially expanding pixels outward along the periphery of the boundary point to obtain a pixel expansion area; wherein the pixel expansion area is a square; Step A2: calculating the average gradient value of the corner pixel points in the pixel expansion area, and determining whether the average gradient value is greater than a first preset threshold; Step A3: If yes, the corner pixel is determined as the tail flame target pixel, and the three pixels around the corner pixel are respectively used as the corner points of the next pixel expansion area, and the execution of steps A1 to A2 is jumped until the calculated average gradient value is less than the first preset threshold value, and the area composed of the tail flame target pixels determined multiple times is determined as the pixel area of ​​the tail flame target.

6. The method according to claim 1, characterized in that After determining the pixel area of ​​the tail flame target, the method further includes: Calculating a pixel average of the tail flame target image, and determining a second preset threshold based on the pixel average; The pixel value of each pixel point outside the pixel area of ​​the tail flame target is compared with the second preset threshold value; if there is a pixel point whose pixel value is greater than the second preset threshold value, the pixel point is determined as the tail flame target pixel.

7. The method according to any one of claims 1 to 6, characterized in that The optical intensity of the pixel area of ​​the tail flame target is calculated by the following formula: Wherein, RADIATION is the optical intensity of the pixel area of ​​the tail flame target, k is the slope of the calibration coefficient between grayscale and intensity, GRAYSUM is the accumulated grayscale value of the pixel area of ​​the tail flame target, GRAYBACKGROUND is the background grayscale value, L is the distance between the tail flame target and the detection camera, FOVV is the detection angle of view of the detection camera in the vertical direction, and FOVH is the detection angle of view of the detection camera in the horizontal direction.

8. A device for calculating the optical characteristics of a tail flame target, characterized in that: include: An acquisition unit, used to acquire detection parameters of the detection camera and several frames of detection images of the tail flame target; A first determining unit is used to determine a frame of image where the center position of the tail flame target is located by using a frame difference method for the plurality of frames of detection images, and determine the frame of image as the tail flame target image; A second determining unit is used to determine a pixel area of ​​the tail flame target in the tail flame target image based on a gradient variation feature of the tail flame target along a center position; A calculation unit is used to calculate the optical intensity of the tail flame target according to the detection parameters, the pixel area of ​​the tail flame target, the distance between the tail flame target and the detection camera, the slope of the calibration coefficient and the transmittance.

9. A computing device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method according to any one of claims 1 to 7.

Images