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Effectiveness Evaluation System Of Military Camouflage Effect Research And System Design

Posted on:2022-12-26Degree:MasterType:Thesis
Country:ChinaCandidate:W YangFull Text:PDF
GTID:2506306776494704Subject:Computer Software and Application of Computer
Abstract/Summary:PDF Full Text Request
Camouflage is a camouflage technique that conceals itself by fusing the target with the visible light background,thus achieving a camouflage technique that confuses the enemy’s judgment.The traditional national military standard uses the field detection method to test the camouflage effect.The process counts the probability of discovering the target by the discriminators at the actual test points,or by the camouflage images collected in the field.The conclusion is greatly affected by the objective environment,and it is impossible to put forward guiding suggestions for some element that causes poor camouflage effect.This paper analyzes and extracts a number of camouflage indicators affecting the camouflage effect,establishes a multi-scheme camouflage evaluation system,can distinguish the advantages and disadvantages of the camouflage scheme,reduce the influence of environmental factors,and puts forward guiding suggestions for the design elements affecting the camouflage effect.Firstly,in the visible light environment,taking the influencing factors of the optical camouflage range and the human eye visual perception system as the index reference,the image is divided into the target image and the background image of 8 adjacent areas.The brightness,color,texture,and edge contour are comprehensively selected to construct the index system.Extract the brightness information in the CIE Lab color space and calculate the brightness contrast value between the target and background images.Quantify the color vector partition in the HSV color space,and calculate the color similarity based on the overlapping area of the color histogram of the two images.The parallel 45° search algorithm is used to obtain the grayscale symbiosis matrix,and the texture similarity between images is calculated.The Canny operator extracts the target edge,and the edge is counted according to the histogram of the boundary direction.The edge contour similarity of the target in the background before and after camouflage is obtained.Secondly,this paper evaluates the multi-attribute decision-making of the scheme index system.First,using the extreme difference transformation method to normalize the initial decision-making attribute matrix to achieve the consistency of the data dimension.Then using the entropy method to allocate weights to the four indicators objectively and then uses the gray correlation analysis and the comprehensive evaluation method of THE TOPSIS method to calculate the evaluation coefficients of each scheme to complete the sorting and optimization between the multi-camouflage schemes,and realize the construction of the theoretical system for the effectiveness evaluation of the military camouflage effect.Finally,according to the theoretical evaluation system’s foundation,this paper designs a universal camouflage effect evaluation system platform.It selects five kinds of camouflage schemes of circular culverts and eight-shaped culverts in the woodland as research objects.The ranking results are obtained for five camouflage schemes and compared by image discrimination method.On the basis of the complex woodland,grassland,desert and snow background,the rationality of the evaluation system and system design is verified.In optical reconnaissance,this paper constructs the effectiveness evaluation system and system design of the military camouflage effect for static targets.Solves the problem that camouflage schemes based on diverse backgrounds cannot be quickly evaluated,reduces the the influence of the objective environment on the human eye observation,and provides a new objective evaluation idea for the field of camouflage evaluation in both theoretical system and system application.
Keywords/Search Tags:Camouflage effect, Index system, Multi-attribute decision making, Entropy method, Grey relational analysis, TOPSIS method
PDF Full Text Request
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