An Evaluation Method for Fusion Feature of Digital Pattern Painting Based on Super-efficiency DEA Model

doi:10.3969/j.issn.1000-1093.2017.11.018

Abstract

Abstract: To evaluate the fusion feature of various digital pattern painting in different backgrounds for the camouflage painting of moving target, the optical images are analyzed, the hue-saturation-value (HSV) model is used, and the image features about color, texture, shape, entropy and complexity are extracted from digital pattern painting and background images. On the basis of super-efficient data envelopment analysis (DEA) model, the efficiency values of one-to-one fusion of digital pattern painting and background images are calculated by taking the differences among the above features in digital pattern painting and background images as the inputs of decision-making unit (DMU). And the reciprocal efficiency values are used as the inputs of new DMU unit, and the efficiency values of fusion of digital pattern painting and background are calculated for the evaluation of comprehensive adaptability of digital pattern painting to background. The efficiency values are checked using the saliency index of image, and two digital pattern painting with maximum and minimum efficiency values are used to camouflage the background. The result shows that the former has lower saliency and better integration in background. Key

Key words: ordnancescienceandtechnology, digitalpatternpainting, featureextraction, super-efficiencyDEAmodel

CLC Number:

E951.4

FENG Hai-chao， ZHAO Zhi-yong， ZHANG Jin-yuan， PAN Guo-qiang. An Evaluation Method for Fusion Feature of Digital Pattern Painting Based on Super-efficiency DEA Model[J]. Acta Armamentarii, 2017, 38(11): 2214-2219.

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第38卷第11期2017 年11月兵工学报ACTA
ARMAMENTARIIVol.38No.11Nov. 2017

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