Evolutionary algorithm-based background generation for robust object detection

Authors:
Taekyung Kim;Seongwon Lee;Joonki Paik
Affiliations:
Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Department of Computer Engineering, College of Electronics and Information, Kwangwoon University, Seoul, Korea;Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

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Abstract

One of the most fundamental image analysis models is background generation that helps to extract information and features in still images and sequential images. Since conventional approaches generate the background from intensity values of the image affected by illumination, the resulting background is often unsatisfactory. In case of background generation with sequential images, noises and the changes of illumination causes errors in the generated background. In this paper we propose an efficient background generation algorithm based on generic algorithm. The proposed algorithm calculates the suitability of changing regions of sequential images, and then causes evolution to the next generation to obtain a clear background. In the proposed evolutionary algorithm, the chromosome includes edges and intensity values of the images so that the algorithm can effectively exclude incorrect information caused by the change of illumination and generates an image of pure background.