Quadtree-based genetic algorithm and its applications to computer vision

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摘要

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.

论文关键词:Genetic algorithm,Ill-posed problems,Image segmentation,Quad-tree,Optimization,Stereo vision,Motion estimation

论文评审过程:Received 9 September 2003, Accepted 12 February 2004, Available online 30 April 2004.

论文官网地址:https://doi.org/10.1016/j.patcog.2004.02.004