基于差分进化和粒子群优化的Freeman链码提取

H. Hasan, H. Haron, S. Hashim
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引用次数: 9

摘要

本文主要研究了利用差分进化和粒子群优化两种软计算方法提取薄二值图像的链码。问题是找到一条覆盖图像所有节点的连续路线。这样做的动机是,当一条路线有许多分支时,找到这样一条路线是很复杂的。文献综述表明,这些方法尚未被用于解决此类问题。此外,结果表明,所提出的粒子群算法比所提出的DE算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Freeman Chain Code Extraction Using Differential Evolution (DE) and Particle Swarm Optimization (PSO)
This paper is focusing on extracting chain codes of a thinned binary image using two soft computing approaches, i.e. Differential Evolution (DE) and Particle Swarm Optimization (PSO). The problem is to find a continuous route which covers all of the nodes of the image. The motivation is that finding such a route is complicated when it has many branches. Literature review shows that these approaches have not been used for solving such problem. In addition, the result shows that the proposed PSO has a better performance than the proposed DE for solving the problem.
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