15 November 2007 Method to reduce over-segmentation of images using immune clonal algorithm
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678649 (2007) https://doi.org/10.1117/12.751155
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Image segmentation is a difficult task. These years, researchers have proposed many segmentation methods based on Evolutionary Algorithms, but most of them used Evolutionary Algorithms to optimize the parameters of an existing segmentation algorithm. This paper tries to use the Evolutionary Algorithms to segment images expecting to explore a new way of image segmentation. The method described in the paper pre-segments the image by Watersheds and then merges it by Immune Clonal Algorithm (ICA). To implement the task, several operators are proposed such as the DC operator, the Proportional Creation of the First generation operator, and fitness function based on JND and average gray value. In the end, the proposed method is compared with another method using GA. The experiments show that the method is effective and the work is significant.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianhua Liang, Jianhua Liang, Shuang Wang, Shuang Wang, Licheng Jiao, Licheng Jiao, } "Method to reduce over-segmentation of images using immune clonal algorithm", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678649 (15 November 2007); doi: 10.1117/12.751155; https://doi.org/10.1117/12.751155
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