CN112950733A - Multi-terrain camouflage pattern generation method suitable for ground equipment - Google Patents

Multi-terrain camouflage pattern generation method suitable for ground equipment Download PDF

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CN112950733A
CN112950733A CN202110225866.2A CN202110225866A CN112950733A CN 112950733 A CN112950733 A CN 112950733A CN 202110225866 A CN202110225866 A CN 202110225866A CN 112950733 A CN112950733 A CN 112950733A
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camouflage
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terrain
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CN112950733B (en
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彭锐晖
房海波
柳林
王向伟
沙香港
赵辉
赵博
陈宗阳
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Harbin Engineering University
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Abstract

The invention discloses a multi-terrain camouflage pattern generation method suitable for ground equipment, which comprises the following steps: s1, dominant color extraction: selecting a typical terrain background image of a region related to the equipment to be camouflaged, and extracting and calculating the multi-terrain camouflage color and the corresponding area proportion thereof; s2, designing a plaque library: based on the bionics principle, acquiring a background typical biological shape image, and constructing a camouflage patch library through matrixing; s3, camouflage pattern generation: and randomly filling the multi-terrain camouflage color and the area ratio thereof of S1 to generate a main color pattern, selecting a biological information patch from the camouflage patch library of S2 to blend the biological information patch into the main color pattern to generate a deformed camouflage color, and carrying out digital processing to obtain the digital camouflage color. The method is simple and quick in calculation, the generated camouflage pattern texture is high in randomness, the size of the camouflage spots is controllable, and the method is suitable for multiple terrain backgrounds. The method and the technical thought of the invention promote the development of the camouflage theory.

Description

Multi-terrain camouflage pattern generation method suitable for ground equipment
Technical Field
The invention belongs to the technical field of image processing and analysis and camouflage design, and particularly relates to a multi-terrain camouflage pattern generation method suitable for ground equipment.
Background
In modern wars, camouflage and stealth technology has become an important component of modern battlefields as a high-technology anti-reconnaissance means. The camouflage stealth technology aims to conceal oneself, deceive and confuse enemies, change the detectable information characteristics of objects such as weaponry and equipment and enable an enemy detection system to be difficult to find or to shorten the finding distance. The camouflage painting is used as the simplest camouflage technology, is one of the simplest and most effective military camouflage protection means, and is an important technology for guaranteeing military strength, resisting modern reconnaissance detection and accurately guiding weapon capture.
The existing camouflage pattern design is mostly focused on the research on a single terrain background, the design method is mature, and a good camouflage effect can be achieved, but the camouflage patterns designed by the method are difficult to simultaneously resist the high-precision reconnaissance and fine capture threats under a plurality of terrain backgrounds in the maneuvering process of equipment, are not suitable for the camouflage of ground equipment, and for the camouflage pattern design of the ground equipment, the visual characteristic information of the equipment, which possibly relates to a regional background image, needs to be comprehensively considered, so that the camouflage protection requirement under an information-based battlefield is difficult to meet.
The multi-terrain camouflage color camouflage pattern design is similar to a traditional camouflage color pattern and comprises three parts, namely camouflage color dominant color extraction, patch design and pattern generation. For the extraction of the main color of the camouflage color, Peng Bian et al [1] extracts the main color of the background by firstly converting the color space into the HSV color space and then by a diversified color histogram method. Zhang Yong, Qi Jia et al [2-3] extract background dominant colors through a K-means clustering method and an improved method thereof, and the study of the scholars on the aspect of extracting the single background camouflage dominant colors achieves good effects, but does not provide a solution for extracting the multiple background camouflage dominant colors. In the problem, Weiyu et al [4] extract the multi-background camouflage dominant color by a clustering algorithm after splicing the background images, but the dominant color extracted by the method may fall into a local minimum value. ZHU et al [5] use frequency distribution and additional weights to perform multiple updates and select the optimal parameters to extract dominant colors, but this method is only applicable to similar terrain. In the plaque design part, Hejrandoost et al [6] fuses multi-background plaque images through thinning, Xue Feng et al [7] generates camouflage plaques by establishing a template library and arranging the plaques in the library by a greedy algorithm, and the plaque design methods all need to extract and fuse the plaques of each background image and are high in calculation complexity. For pattern generation, a generation method such as random fill, corresponding fill, or fill in which the number of pixel colors in a basic cell is the largest is generally used.
Reference to the literature
[1]PENG Bian,JIN Yi,ZHANG Nairen.Fuzzy c-means clustering based digital camouflage pattern design and its evaluation[C]//IEEE International Conference on Signal Processing,Yantai China,2010:1017-1020.
[2] Zhang Yong, Wu Wen Jian, Liu Shiming, camouflage color selection [ J ] based on improved K-means clustering analysis computer engineering and applications, 2009,45(006): 210-.
[3]QI Jia,LIN Ziqiang,Hu Jianghua,,et al.Design and Evaluation of Facial Camouflage Pattern[C]//.International Conference on Artificial Intelligence and Computer Science(AICS 2019),Hubei Zhongke Institute of Geology and Environment Technology,2019:4.
[4] Method for extracting theme colors and generating camouflage colors from multiple pictures under the background of visible light: china, CN201910898945.2[ P ] 2020-01-21.
[5]ZHU W,ZHANG Y,ZHU H,et al.All-terrain camouflage design on frequency analysis[C]//Control&Decision Conference.IEEE,Yinchuan China,2016:3102-3105.
[6]Hejrandoost AA,Safabakhsh R.Thinning Based Multipurpose Camouflage Pattern Design[C]//Machine Vision&Image Processing.IEEE,Iranian,2012:1-5.
[7]Xue F,Xu S,Luo Y T,et al.Design of digital camouflage by recursive overlapping of pattern templates[J].Neurocomputing,2015,172(JAN.8):262-270.
Disclosure of Invention
The invention aims to solve the problem that the existing camouflage pattern design method of the ground equipment under a single background is difficult to meet the camouflage requirement under the multi-terrain background environment, and provides a multi-terrain deformation and digital camouflage pattern generation method suitable for the ground equipment. The method is divided into three modules, and the dominant color extraction: selecting a typical background image of a to-be-disguised device possibly related to a region, and extracting multi-terrain camouflage color dominant colors and area ratios thereof through differential analysis of background dominant colors; designing a plaque library: based on the bionics principle, typical biological shape pictures are collected, and a camouflage plaque library is constructed; and (3) generation of camouflage patterns: and randomly filling and generating a main color pattern based on the multi-terrain camouflage color main color and the area ratio thereof, selecting a biological information patch from the patch library, blending the biological information patch into the camouflage color main color pattern to generate a deformed camouflage color, and performing digital processing to obtain the digital camouflage color.
The purpose of the invention is realized as follows:
a method of generating a multi-terrain camouflage pattern for use with surface equipment, comprising the steps of:
s1, extracting a dominant color;
s1.1, analyzing the terrain environment where the ground equipment to be disguised is located, collecting a plurality of terrain background images, and respectively carrying out preprocessing operation on each background image, wherein the preprocessing operation comprises the following steps: size normalization and image denoising; selecting a typical image from each terrain background, and storing the typical image in a sequence P, wherein P is { I ═ Ii1,2, a, N, where N represents the number of selected background images;
s1.2, adopting an image color quantization algorithm to carry out quantization on I in the selected background image sequenceiAre respectively provided withAnd performing color quantization processing, quantizing the color data to K background dominant colors, recording color values and corresponding area proportions of the background dominant colors, and recording the color values and the corresponding area proportions as:
Figure BDA0002956051740000031
Figure BDA0002956051740000032
the color value representing the dominant color of the background is
Figure BDA0002956051740000033
The three-dimensional vector of the composition,
Figure BDA0002956051740000034
representing an area ratio of the background dominant color;
s1.3. for different background images IiBackground dominant color of
Figure BDA0002956051740000035
Performing color difference analysis, and calculating the main color of the multi-terrain camouflage color and the corresponding area proportion thereof according to the analysis result;
the average color difference formula is used as a measurement function, the color difference between the background dominant colors is analyzed, and the smaller the measurement function value is, the smaller the difference between the two background dominant colors is;
setting and selecting two different terrain background images Ii、IjAfter the color quantization processing of step S1.2, the color value and the corresponding area ratio of the background dominant color are respectively
Figure BDA0002956051740000036
The metric function formula can be derived as follows:
Figure BDA0002956051740000037
finding the background dominant color combination which minimizes the overall color difference according to the definition of the color similarity metric function,
the optimization process formula is described as follows:
Figure BDA0002956051740000038
the above formula represents substituting into the background image IjAll permutation combinations of the background dominant colors are searched for variables k1', k2', k3', a., kK', k1, k2, k3, a., kK which minimize the overall calculation result, i.e. I is carried outi1,2,3, K background dominant colors and IjThe k1, k2, k3, ·, kK background dominant color combinations;
wherein K1', K2', K3',. kK' is for {1,2, 3.. K }, and K represents the number of multi-background camouflage dominant colors;
according to the above optimization process, the background dominant color combination with the minimum overall color difference is:
Figure BDA0002956051740000041
the multi-terrain camouflage color dominant color is obtained by calculating the mean value of each background dominant color combinationsAnd area ratio psS ∈ {1, 2., K }, the formula is expressed as follows:
s2, designing a plaque library;
based on the principle of bionics, a typical biological shape image of a background is collected, the typical biological shape image is preprocessed and trimmed, and then the biological shape image is converted into a biological information patch by using a matrixing method;
the algorithm is described as follows:
step 1: inputting a biological shape image AmAnd M belongs to {1,2, 3., M }, wherein M is the total number of the biological shape images to be processed, the human-computer interactive frame selects the minimum circumscribed rectangle containing all biological shapes, and outputs the rectangle which is named as A _ Sm；
Step 2: for A _ SmCarrying out size normalization processing, setting the size L x L, namely the size of the biological information patch, then carrying out decoloring processing, and converting an RGB color image into a gray image;
and step 3: performing image self-adaptive threshold segmentation algorithm on the gray level image to segment out biological shapeThe contour and the segmentation result are recorded as A _ cutmConverting A _ cutmIs a binary matrix, namely the biological information plaque, and is marked as A _ resultmA _ result is addedmSequentially storing the data into a plaque library A _ CLUB;
and 4, step 4: circularly executing the steps 1-3 until all the M images containing the biological shape information are processed and stored in the plaque library, and finishing the circular process;
s3, generating camouflage patterns;
s3.1, generating a dominant color pattern;
firstly, dividing the size of the dominant color pattern and the size of the mosaic unit to obtain the number of the mosaic unit in the dominant color pattern, wherein the formula is as follows:
Figure BDA0002956051740000042
wherein o x q is the size of the dominant color pattern, and λ x λ is the size of the mosaic unit;
then the number n of mosaic units of each multi-terrain camouflage color dominant color is distributed according to the area proportion calculated in the step S1.3r，r∈{1,2,...,K}；
Finally, randomly selecting n in the dominant color patternrA mosaic unit filled with corresponding multi-terrain camouflage main colorsUntil all the mosaic units are filled, the main color pattern X is generated;
s3.2, generating a deformed camouflage pattern;
after the dominant color pattern is generated, a biological information plaque A _ result is randomly selected from the plaque librarymAnd fusing the plaque characteristics into the dominant color pattern by a mathematical morphology method, and performing a specific fusion process by adopting an open-close operation formula, wherein the formula is expressed as follows:
I_com＝X·(XοA_resultm)
i _ com represents the generated deformed camouflage pattern, operator. Representing a morphological open operation, an operator, representing a morphological closed operation;
s3.3, generating a digital camouflage pattern;
generating a digital camouflage pattern through digital processing after the deformed camouflage pattern is generated;
firstly, determining the size d of a basic unit of the digital camouflage color, then, processing the deformed camouflage color pattern in blocks, wherein the size of each block is the size of the basic unit of the digital camouflage color, and the processing process of the blocks is as follows:
counting the pixels with the most occurrence times in the block and assigning the color values of the pixels to all the pixels in the block;
the operation is circulated until all blocks in the deformed camouflage pattern are completely executed, and the processed image is the digital camouflage pattern;
further: the method for calculating the dominant color and the area ratio of the multi-background camouflage color in the step S1.3 is not limited to two different terrain backgrounds, and is also suitable for extracting the dominant color of more than two terrain backgrounds. .
Further: step S3.2 can flexibly control the size of the patch in the deformed camouflage pattern by controlling the ratio of the size L of the biological information patch to the size lambda of the mosaic unit in the fusion process, and the size of the mosaic unit is generally set to be smaller than that of the biological information patch in consideration of the fact that the size of the patch in the deformed camouflage pattern cannot be too large, and the size setting can refer to: 0.5 x L is not more than lambda and is less than L.
Further: step S3.3 in the process of blocking, the pixels with the largest number of occurrences in the statistical block follow the following rules:
(1) if only one pixel exists in the block with the largest occurrence frequency, replacing all pixels in the block with the pixel with the largest occurrence frequency;
(2) and if the pixels with the most occurrence times in the block have G types, and G belongs to {2, 3., K }, randomly selecting one of the G types of pixels to replace all the pixels in the block.
Further: step S3.3 the blocking process uses sequential operations, i.e. from left to right and top to bottom in the image matrix.
Compared with the prior art, the invention has the beneficial effects that:
(1) the method measures the color similarity among the background dominant colors of a plurality of terrain backgrounds by adopting an average color difference formula, obtains the color similarity of the multi-terrain camouflage color dominant colors and the area proportion thereof by adopting a mean value calculation method according to a measurement result, and fuses the color information of the plurality of terrain backgrounds with the camouflage dominant colors, so that the dynamic equipment to be disguised has better color fusion degree for each type of terrain, and the dynamic disguising effect is realized.
(2) Based on the bionics principle, the biological shape is used as the digital and deformed camouflage pattern patch, the processing of image patch segmentation, extraction, fusion and the like on each terrain background image is avoided, the calculation simplicity is improved, only direct calling is needed in the subsequent camouflage color generation process of one-time patch library manufacturing, and the real-time performance of camouflage pattern generation is enhanced.
(3) Before generating the digital and deformed camouflage color, the method firstly utilizes the multi-terrain camouflage color dominant color and the area ratio thereof to randomly generate the dominant color pattern, thereby enhancing the randomness of the camouflage color texture and improving the camouflage effect.
(4) The method adopts mathematical morphology operation to fuse the biological information patch into the dominant color pattern to generate the deformed camouflage, so that the size of the camouflage patch is flexible and controllable, the mathematical morphology only relates to logical relation operation, the arithmetic operation speed is high, and the camouflage generation efficiency is improved.
(5) According to the method for generating the multi-terrain deformation and digital camouflage patterns, the generated camouflage patterns are suitable for the multi-variability terrain background, reference can be provided for camouflage design of various ground equipment, and the method is also suitable for camouflage pattern design of other military targets under various different terrain backgrounds.
Drawings
FIG. 1 is a block flow diagram of a method for generating a multi-terrain camouflage pattern suitable for use with surface equipment in accordance with the present invention;
FIG. 2 is a diagram of a typical terrain background picture taken in an embodiment of the present invention;
FIG. 3 is a background dominant color result after background image color quantization according to an embodiment of the present invention;
FIG. 4 illustrates multi-terrain camouflage mass tone in accordance with an embodiment of the present invention;
FIG. 5 is a flow chart of a plaque library design algorithm in an embodiment of the present invention;
FIG. 6 is a patch diagram of segmentation results and biological information in the design of a patch library according to an embodiment of the present invention;
FIG. 7 is a dominant color pattern in an embodiment of the present invention;
FIG. 8 is a schematic representation of a pattern of a plurality of patterns of the present invention;
FIG. 9 is a diagram illustrating the digitizing result of the deformed camouflage pattern according to an embodiment of the present invention;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Referring to fig. 1, a method for generating a multi-terrain-deformation digital camouflage color suitable for ground equipment includes the following steps:
s1, extracting a dominant color;
s1.1, analyzing the terrain environment where the ground equipment to be disguised is located, collecting a plurality of terrain background images, and respectively carrying out preprocessing operation on the background images, wherein the preprocessing operation comprises the following steps: size normalization and image denoising; selecting a typical image from each terrain background, and storing the typical image in a sequence P, wherein P is { I ═ Ii1,2, a, N, where N represents the number of selected background images;
the ground equipment to be disguised mainly comprises ground equipment such as armored vehicles, tanks, military communication vehicles, military transport vehicles and the like, and comprises dynamic and static ground equipment;
the background image preprocessing aims at unifying the size of a background image and removing noise interference of imaging equipment and an external environment on the background image;
the typical terrain background images selected in the embodiment of the present invention are shown in fig. 2(a) and (b), and are forest land and grassland type backgrounds, that is, the sequence P ═ I1，I2}，N＝2；
Setting the size o q of a background image as 300, and denoising the image sequence by adopting a wavelet threshold denoising mode;
s1.2, adopting an image color quantization algorithm to carry out I in a background image sequenceiAnd respectively carrying out color quantization processing, quantizing the color data to K background dominant colors, recording the color values and the corresponding area proportions of the background dominant colors, and recording as follows:
Figure BDA0002956051740000071
Figure BDA0002956051740000072
the color value representing the dominant color of the background is
Figure BDA0002956051740000073
The three-dimensional vector of the composition,
Figure BDA0002956051740000074
representing an area ratio of the background dominant color;
the background dominant color number K generally ranges from: k is more than or equal to 3 and less than or equal to 6;
based on the visual characteristics of human eyes and the design specifications of the camouflage color, the color of the background picture can be represented by a plurality of dominant colors, and the camouflage effect of the camouflage color is not reduced by using the dominant colors;
the color types of the background images are thousands of, the real-time property of the generation of the camouflage patterns is considered, and the color types are compressed by adopting an image color quantization algorithm;
the image color quantization algorithm comprises: quantizing a color histogram, K-means clustering, FCM clustering, ISODATA clustering and the like;
considering the real-time and accuracy requirements of the generation of the camouflage pattern, the K-means clustering algorithm which is mature and simple to calculate is preferentially selected in the embodiment, and the initial clustering center selects a point with large chromatic aberration in the image, so that the color quantification accuracy is improved;
in the embodiment of the present invention, a K-means clustering algorithm quantizes colors of a background image, where K is 3, a background dominant color result is shown in fig. 3(a) and (b), and specific background dominant color values and area accounts for the following table 1:
TABLE 1 background dominant color values and area ratios
Figure BDA0002956051740000081
S1.3. for different background images IiBackground dominant color of
Figure BDA0002956051740000082
Performing color difference analysis, and calculating the main color of the multi-terrain camouflage color and the corresponding area proportion thereof according to the analysis result;
the average color difference formula is used as a measurement function, the color difference between the background dominant colors is analyzed, and the smaller the measurement function value is, the smaller the difference between the two background dominant colors is;
setting and selecting two different terrain background images Ii、IjAfter the color quantization processing of step S1.2, the color value and the corresponding area ratio of the background dominant color are respectively
Figure BDA0002956051740000091
The metric function formula can be derived as follows:
Figure BDA0002956051740000092
when the terrain background is N pieces, the color value and the corresponding area proportion of the dominant color of the background are respectively
Figure BDA0002956051740000093
The metric function is formulated as:
Figure BDA0002956051740000094
finding the background dominant color combination which minimizes the overall color difference according to the definition of the color similarity metric function,
the optimization process formula is described as follows:
Figure BDA0002956051740000095
the above formula represents substituting into the background image IjAll permutation combinations of the background dominant colors are searched for variables k1', k2', k3', a., kK', k1, k2, k3, a., kK which minimize the overall calculation result, i.e. I is carried outi1,2,3, K background dominant colors and IjThe k1, k2, k3, ·, kK background dominant color combinations;
wherein K1', K2', K3',. kK' is for {1,2, 3.. K }, and K represents the number of multi-background camouflage dominant colors;
according to the above optimization process, the background dominant color combination with the minimum overall color difference is:
Figure BDA0002956051740000096
in the embodiment of the present invention, the number N of the terrain background images is 2, and K is 3, that is, the color value and the corresponding area ratio of the dominant color of the background are respectively
Figure BDA0002956051740000097
Substituting the background dominant color of the background image 2 according to the above optimization process
Figure BDA0002956051740000098
All permutations of (a), the variable with the least difference in colour: k1 ═ 2, k2 ═ 3, k3 ═ 1, i.e., k1 ═ 2, k2 ═ 3, and k3 ═ 1;
in the embodiment of the present invention, the combination of the background main colors with the minimum overall color difference is:
Figure BDA0002956051740000101
the multi-terrain camouflage color dominant color is obtained by calculating the mean value of each background dominant color combinationsAnd area ratio psS ∈ {1, 2., K }, the formula is expressed as follows:
Figure BDA0002956051740000102
Figure BDA0002956051740000103
from the above formula, the multi-terrain camouflage dominant color and the area ratio in the embodiment of the present invention are shown in table 2 below, for example:
TABLE 2 Multi-terrain camouflage mass tone and area ratio
Figure BDA0002956051740000104
The multi-terrain camouflage dominant color in the embodiment is shown in fig. 4;
the multi-background camouflage color dominant color and area ratio calculation method is not limited to two terrain backgrounds, and is also suitable for dominant color extraction of more than two terrain backgrounds.
S2, designing a plaque library;
based on the bionics principle, typical biological shape images of a background are collected, preprocessed and trimmed, and then the biological shape images are converted into biological information patches by using a matrixing method;
the algorithm is described as follows:
step 1: inputting a biological shape image AmAnd M belongs to {1,2, 3., M }, wherein M is the total number of the biological shape images to be processed, the human-computer interactive frame selects the minimum circumscribed rectangle containing all biological shapes, and outputs the rectangle which is named as A _ Sm；
Step 2: for A _ SmCarrying out size normalization processing, setting the size L x L, namely the size of the biological information patch, then carrying out decoloring processing, and converting an RGB color image into a gray image;
and step 3: performing image self-adaptive threshold segmentation algorithm on the gray level image to segment out the biological shape contour, and recording the segmentation result as A _ cutmConverting A _ cutmIs a binary matrix, namely the biological information plaque, and is marked as A _ resultmA _ result is addedmSequentially storing the data into a plaque library A _ CLUB;
and 4, step 4: circularly executing the steps 1-3 until all the M images containing the biological shape information are processed and stored in the plaque library, and finishing the circular process;
the typical biological shape image of the background is an animal and plant shape image collected in a plurality of types of terrain backgrounds where the ground equipment to be camouflaged is located;
in the embodiment of the invention, the biological shape image is a willow leaf, poplar leaf, maple leaf and tiger stripe shape image;
the camouflage patch is manufactured according to the biological shape image, so that the process of generating the patch by processing image patch segmentation, extraction and the like on each terrain background image is avoided, the calculation simplicity is improved, and the bionic source basis of the camouflage is met.
The patch library is only required to be manufactured once and is directly called in the subsequent camouflage color generation process;
a flow chart of a specific plaque library design algorithm is shown in FIG. 5;
in this embodiment, patch library design is performed on images of willow leaves, poplar leaves, maple leaves, and tiger stripes, that is, M is 4, the size L of the biometric patch is 10 pixels, and the segmentation result a _ cut is obtainedmAnd a biological information patch A _ resultmAs shown in FIGS. 6(a), (b), (c), (d), respectively;
s3, generating deformation and digital camouflage;
s3.1, generating a dominant color pattern;
firstly, dividing the size of the dominant color pattern and the size of the mosaic unit to obtain the number of the mosaic unit in the dominant color pattern, wherein the formula is as follows:
Figure BDA0002956051740000121
wherein o x q is the size of the dominant color pattern, and λ x λ is the size of the mosaic unit;
then the number n of mosaic units of each multi-terrain camouflage color dominant color is distributed according to the area proportion calculated in the step S1.3r，r∈{1,2,...,K}；
Finally, randomly selecting n in the dominant color patternrA mosaic unit filled with corresponding multi-terrain camouflage main colorsUntil the mosaic units are completely filled, the main color pattern X is generated;
in this embodiment, the unit of o × q is 300 × 300, λ × λ is 5 × 5, and the above formula is substituted to obtain n × 3600, and a mosaic of each multi-terrain dominant color can be assigned according to the area ratio of the multi-terrain camouflage dominant colorThe number of units is: n is1＝3600×0.4929＝1774、n2＝3600×0.3147＝1133、n3＝3600×0.1924＝693；
The dominant color pattern generated in the present embodiment is shown in fig. 7;
s3.2, generating a deformed camouflage pattern;
after the dominant color pattern is generated, a biological information plaque A _ result is randomly selected from the plaque librarymAnd fusing the plaque characteristics into the dominant color pattern by a mathematical morphology method, and performing a specific fusion process by adopting an open-close operation formula, wherein the formula is expressed as follows:
I_com＝X·(XοA_resultm)
i _ com represents the generated deformed camouflage pattern, an operator represents morphological open operation, and the operator represents morphological close operation;
the patch size in the camouflage pattern that warp is nimble to be controlled to the ratio of accessible control bioinformation patch size L and mosaic unit size lambda among the fusion process, considers that the patch size can not be too big in the camouflage pattern that warp, generally sets up mosaic unit size and is less than bioinformation patch size, and the size setting can refer to: 0.5 x L is more than or equal to lambda and less than L;
if the blended camouflage patterns have small spots and noise points, smoothing can be continuously carried out through morphological closed operation, and the small spots are combined, so that the generated camouflage patterns are more reasonable and natural on the basis of keeping the bionic texture, and the morphological closed operation formula is as follows:
I_com1＝I_com·se
in the formula, se is a structural element,
Figure BDA0002956051740000131
i _ com1 is the smoothed deformed camouflage pattern;
in the embodiment of the invention, willow leaf patches, tiger stripes and maple leaf patches in a patch library are respectively selected to carry out fusion operation, and the generated deformed camouflage patterns are shown in figures 8(a), (b) and (c);
s3.3, generating a digital camouflage pattern;
generating a digital camouflage pattern through digital processing after the deformed camouflage pattern is generated;
firstly, determining the size d of a basic unit of the digital camouflage color, then, processing the deformed camouflage color pattern in blocks, wherein the size of each block is the size of the basic unit of the digital camouflage color, and the processing process of the blocks is as follows:
counting the pixels with the most occurrence times in the block and assigning the color values of the pixels to all the pixels in the block;
the operation is circulated until all blocks in the deformed camouflage pattern are completely executed, and the processed image is the digital camouflage pattern;
the statistical blocking processing process adopts sequential operation, namely from left to right and from top to bottom in an image matrix;
the most frequent pixels in the statistical block follow the following rules:
(1) if only one pixel exists in the block with the largest occurrence frequency, replacing all pixels in the block with the pixel with the largest occurrence frequency;
(2) and if the pixels with the most occurrence times in the block have G types, and G belongs to {2, 3., K }, randomly selecting one of the G types of pixels to replace all the pixels in the block.
In the embodiment of the present invention, the size d × d of the basic unit of the digital camouflage is set to 3 × 3 (pixels), and the results of the deformed camouflage digitization on the above-mentioned willow leaf, tiger stripe, and maple leaf patches are shown in fig. 9(a), (b).
According to the method, deformation and digital camouflage patterns suitable for a plurality of terrain background environments are generated through the steps of multi-terrain camouflage main color extraction, bionic patch library design, random camouflage pattern generation and the like, the method can provide reference for camouflage pattern design of various ground equipment, and is also suitable for camouflage pattern design of other static military targets under different terrain backgrounds.
The invention discloses a multi-terrain camouflage pattern generation method suitable for ground equipment, which comprises the following steps: s1, dominant color extraction: selecting a typical terrain background image of a region related to the equipment to be camouflaged, and extracting and calculating the multi-terrain camouflage color and the corresponding area proportion thereof; s2, designing a plaque library: based on the bionics principle, acquiring a background typical biological shape image, and constructing a camouflage patch library through matrixing; s3, camouflage pattern generation: and randomly filling the multi-terrain camouflage color and the area ratio thereof of S1 to generate a main color pattern, selecting a biological information patch from the camouflage patch library of S2 to blend the biological information patch into the main color pattern to generate a deformed camouflage color, and carrying out digital processing to obtain the digital camouflage color. The method is simple and quick in calculation, the generated camouflage pattern texture is high in randomness, the size of the camouflage spots is controllable, and the method is suitable for multiple terrain backgrounds. The method and the technical thought of the invention promote the development of the camouflage theory.
The invention is not the best known technology.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.

Claims (5)

1. A multi-terrain camouflage pattern generation method suitable for ground equipment is characterized by comprising the following steps:
s1, extracting a dominant color;
s1.1, analyzing the terrain environment where the ground equipment to be disguised is located, collecting a plurality of terrain background images, selecting a typical image for each terrain background, and storing the typical image into a sequence P, wherein P is { I ═ I }i1,2, a, N, where N represents the number of selected background images; preprocessing the selected background image, including size normalization and image denoising;
s1.2, adopting an image color quantization algorithm to carry out I treatment on the preprocessed background image sequenceiAnd respectively carrying out color quantization processing, quantizing the color data to K background dominant colors, recording the color values and the corresponding area proportions of the background dominant colors, and recording as follows:
Figure FDA0002956051730000011
k∈(1,2,...,K)，fi ka color value representing the dominant color of the background is represented by fi k[R]、fi k[G]、fi k[B]The three-dimensional vector of the composition,
Figure FDA0002956051730000012
representing an area ratio of the background dominant color;
s1.3. for different background images IiBackground dominant color fi kPerforming color difference analysis, and calculating the main color of the multi-terrain camouflage color and the corresponding area proportion thereof according to the analysis result;
the average color difference formula is used as a measurement function, the color difference between the background dominant colors is analyzed, and the smaller the measurement function value is, the smaller the difference between the two background dominant colors is;
setting and selecting two different terrain background images Ii、IjAfter the color quantization processing of step S1.2, the color value and the corresponding area ratio of the background dominant color are respectively
Figure FDA0002956051730000013
The metric function formula can be derived as follows:
Figure FDA0002956051730000014
finding the background dominant color combination which minimizes the overall color difference according to the definition of the color similarity metric function,
the optimization process formula is described as follows:
Figure FDA0002956051730000015
the above formula represents substituting into the background image IjAll permutation combinations of background dominant colorsI, searching for variables k1', k2', k3',. and kK', which are k1, k2, k 3.. and kK and minimize the overall calculation result, namely performing Ii1,2,3, K background dominant colors and IjThe k1, k2, k3, ·, kK background dominant color combinations;
wherein K1', K2', K3',. kK' is for {1,2, 3.. K }, and K represents the number of multi-background camouflage dominant colors;
according to the above optimization process, the background dominant color combination with the minimum overall color difference is:
Figure FDA0002956051730000021
the multi-terrain camouflage color dominant color is obtained by calculating the mean value of each background dominant color combinationsAnd area ratio psS ∈ {1, 2., K }, the formula is expressed as follows:
Figure FDA0002956051730000022
Figure FDA0002956051730000023
s2, designing a plaque library;
based on the principle of bionics, firstly, a typical biological shape image of a background is collected, the typical biological shape image is preprocessed and trimmed, and then the biological shape image is converted into a biological information patch by using a matrixing method;
the specific process of designing the plaque library is described as follows:
step 1: inputting a biological shape image AmAnd M belongs to {1,2, 3., M }, wherein M is the total number of the biological shape images to be processed, the human-computer interactive frame selects the minimum circumscribed rectangle containing all biological shapes, and outputs the rectangle which is named as A _ Sm；
Step 2: for A _ SmPerforming size normalization to set size L, which is the size of the biological information patch, performing decolorizing treatment, and converting from RGB color imageIs a gray scale image;
and step 3: performing image self-adaptive threshold segmentation algorithm on the gray level image to segment out the biological shape contour, and recording the segmentation result as A _ cutmConverting A _ cutmIs a binary matrix, namely the biological information plaque, and is marked as A _ resultmA _ result is addedmSequentially storing the data into a plaque library A _ CLUB;
and 4, step 4: circularly executing the steps 1-3 until all the M images containing the biological shape information are processed and stored in the plaque library, and finishing the circular process;
s3, generating camouflage patterns;
s3.1, generating a dominant color pattern;
firstly, dividing the size of the dominant color pattern and the size of the mosaic unit to obtain the number of the mosaic unit in the dominant color pattern, wherein the formula is as follows:
Figure FDA0002956051730000031
in the formula, o x q is the size of the primary color pattern, and lambda x lambda is the size of the mosaic unit;
then distributing the number n of mosaic units of each multi-terrain camouflage color dominant color according to the area proportion calculated in the step S1.3r，r∈{1,2,...,K}；
Finally, randomly selecting n in the dominant color patternrA mosaic unit filled to the corresponding multi-terrain camouflage main colorsUntil all the mosaic units are filled, the main color pattern X is generated;
s3.2, generating a deformed camouflage pattern;
after the dominant color pattern is generated, a biological information plaque A _ result is randomly selected from the plaque librarymAnd fusing the plaque characteristics into the dominant color pattern by a mathematical morphology method, and performing a specific fusion process by adopting an open-close operation formula, wherein the formula is expressed as follows:
Figure FDA0002956051730000032
i _ com represents the generated deformed camouflage pattern, operator. Representing a morphological open operation, an operator, representing a morphological closed operation;
s3.3, generating a digital camouflage pattern;
generating a digital camouflage pattern through digital processing after the deformed camouflage pattern is generated;
firstly, determining the size d of a basic unit of the digital camouflage color, then, processing the deformed camouflage color pattern in blocks, wherein the size of each block is the size of the basic unit of the digital camouflage color, and the processing process of the blocks is as follows:
counting the pixels with the most occurrence times in the block and assigning the color values of the pixels to all the pixels in the block;
and circulating the operations until all the blocks in the deformed camouflage pattern are completely executed, wherein the processed image is the digital camouflage pattern.
2. The method of claim 1, wherein the method comprises: the method for calculating the dominant color and the area ratio of the multi-background camouflage color in the step S1.3 is not limited to two different terrain backgrounds, and is also suitable for extracting the dominant color of more than two terrain backgrounds.
3. The method of claim 1, wherein the method comprises: step S3.2 can flexibly control the size of the patch in the deformed camouflage pattern by controlling the ratio of the size L of the biological information patch to the size lambda of the mosaic unit in the fusion process, and the size of the mosaic unit is generally set to be smaller than that of the biological information patch in consideration of the fact that the size of the patch in the deformed camouflage pattern cannot be too large, and the size setting can refer to: 0.5 x L is not more than lambda and is less than L.
4. The method of claim 1, wherein the method comprises: step S3.3 in the process of blocking, the pixels with the largest number of occurrences in the statistical block follow the following rules:
(1) if only one pixel exists in the block with the largest occurrence frequency, replacing all pixels in the block with the pixel with the largest occurrence frequency;
(2) and if the pixels with the most occurrence times in the block have G types, and G belongs to {2, 3., K }, randomly selecting one of the G types of pixels to replace all the pixels in the block.
5. The method of claim 4, wherein the method comprises: the blocking process uses sequential operations, i.e., from left to right and top to bottom in the image matrix.
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