期刊
PATTERN RECOGNITION
卷 37, 期 8, 页码 1723-1733出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2004.02.004
关键词
genetic algorithm; ill-posed problems; image segmentation; quad-tree; optimization; stereo vision; motion estimation
Many computer vision problems can be formulated as optimization problems. Presented in this paper is a new framework based on the quadtree-based genetic algorithm that can be applied to solve many of these problems. The proposed algorithm incorporates the quadtree structure into the conventional genetic algorithm. The solutions of image-related problems are encoded through encoding the corresponding quadtrees, and therefore, the 2D locality within a solution can be preserved. Examples addressed using the proposed framework include image segmentation, stereo vision, and motion estimation. In all cases, encouraging results are obtained. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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