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A new image segmentation algorithm based on modified seeded region growing and particle swarm optimization

机译:一种基于改进的种子区域生长和粒子群优化的新图像分割算法

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Image Segmentation, a basic technique for many real world applications, has been considered in this paper. The Seeded Region Growing (SRG) algorithm, as the first and probably the simplest region growing algorithm, faces three important problems: the position of seeds, the number of seeds, and region growing strategy. Two new versions of SRG are introduced here to solve the multi seeded region growing problem, and also region growing strategy. Then Particle Swarm Optimization is utilized to solve the localization problem. Experimental results show that the proposed method is successfully applied to gray scale image segmentation.
机译:在本文中考虑了图像分割,许多真实世界应用的基本技术。种子区域生长(SRG)算法,作为第一且可能是最简单的区域生长算法,面临三个重要问题:种子的位置,种子数量和区域生长策略。这里介绍了两个新的SRG版本,以解决多种子区域生长问题,以及地区生长策略。然后利用粒子群优化来解决本地化问题。实验结果表明,该方法成功应用于灰度图像分割。

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