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Proceedings Paper

The relationship study between image features and detection probability based on psychology experiments
Author(s): Wei Lin; Yu-hua Chen; Ji-yuan Wang; Hong-sheng Gao; Ji-jun Wang; Rong-hua Su; Wei Mao
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Paper Abstract

Detection probability is an important index to represent and estimate target viability, which provides basis for target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great difference will often exist in the datum obtained. By means of studying the relationship between image features and perception quantity based on psychology experiments, the probability model has been established, in which the process is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four feature similarity degrees between target and background were defined. Secondly, the relationship between single image feature similarity degree and perception quantity was set up based on psychological principle, and psychological experiments of target interpretation were designed which includes about five hundred people for interpretation and two hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which include images with single brightness feature difference, images with single chromaticity feature difference, images with single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and experimental results, the relationship between perception quantity with target detection probability has been found. With the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the model quickly and objectively.

Paper Details

Date Published: 26 April 2011
PDF: 10 pages
Proc. SPIE 8055, Optical Pattern Recognition XXII, 80550S (26 April 2011); doi: 10.1117/12.883358
Show Author Affiliations
Wei Lin, Beijing Institute of Technology (China)
Beijing Canbao Architecture Design Institution (China)
Yu-hua Chen, Beijing Canbao Architecture Design Institution (China)
Ji-yuan Wang, Beijing Canbao Architecture Design Institution (China)
Hong-sheng Gao, Beijing Canbao Architecture Design Institution (China)
Ji-jun Wang, Beijing Canbao Architecture Design Institution (China)
Rong-hua Su, Beijing Canbao Architecture Design Institution (China)
Wei Mao, Beijing Canbao Architecture Design Institution (China)


Published in SPIE Proceedings Vol. 8055:
Optical Pattern Recognition XXII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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