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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kim, T., Lee, S., Paik, J. (2006). Evolutionary Algorithm-Based Background Generation for Robust Object Detection. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_67
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DOI: https://doi.org/10.1007/11816157_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
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