A Surendra-based Improved Detection Method of Moving Target Camouflage Effect

doi:10.3969/j.issn.1000-1093.2017.01.025

Abstract

Abstract: The existing camouflage detection is mainly for static targets, which can not objectively reflect the effectiveness of camouflage in combat operations of mobile equipment. The moving object detection technology and the principle of camouflage are synthetical used for target detection, and the military truck model is used as the research object. Based on Surendra background update model and Lab three-channel, a new method for detecting the camouflage effect of moving objects is proposed. According to the established experimental system, the Euclidean distance between the shape feature parameters of the military truck before and after camouflage is calculated, and the average Euclidean distance of the image sequences is 189.45. It showes that the shape feature parameters of the moving objects before and after camouflage are very different. The target after camouflage has a certain characteristics of dynamic deformation camouflage. At the same time, with the aid of the performance evaluation module, the correlation coefficient range of target image before and after camouflage is 0.003 5~0.127 5. The scientific and reliability of the detection method is proved. According to the principle of moving target detection algorithm, it can be known that the images of moving target after camouflage has a certain fusion with the images of central background. Key

Key words: ordnancescienceandtechnology, movingtarget, patternpaintingcamouflage, digitalcamouflage, effectdetection

CLC Number:

E951.4

YANG Jun-tang, XU Wei-dong, QU Yang, CUI Guang-zhen. A Surendra-based Improved Detection Method of Moving Target Camouflage Effect[J]. Acta Armamentarii, 2017, 38(1): 190-194.

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第38卷
第1期2017 年1月兵工学报ACTA
ARMAMENTARIIVol.38No.1Jan.2017

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