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Color disease spot image segmentation algorithm based on chaotic particle swarm optimization and FCM

机译:基于混沌粒子群优化和FCM的彩色疾病点图像分割算法

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摘要

Aiming at solving the problems of complex image background and difficulties in the later image segmentation, an image segmentation algorithm based on the chaotic particle swarm algorithm and fuzzy clustering is proposed. First, the color space is converted from the RGB color space into the HIS color space. Then, a hybrid algorithm consisted of chaotic particle swarm optimization and fuzzy clustering is introduced. Each color component is processed by the algorithm, and the corresponding partition graph is obtained. Finally, the color space is converted into the RGB color space to achieve the segmentation effect. Experimental results show that the new algorithm has higher accuracy to segment the image and has good robustness to noises.
机译:旨在解决复杂图像背景的问题和稍后的图像分割中的困难,提出了一种基于混沌粒子群算法和模糊聚类的图像分割算法。首先,颜色空间从RGB颜色空间转换为他的颜色空间。然后,引入了由混沌粒子群优化和模糊聚类组成的混合算法。每个颜色分量由算法处理,并且获得相应的分区图。最后,颜色空间被转换为RGB颜色空间以实现分割效果。实验结果表明,新算法具有更高的准确性来分割图像并对噪音具有良好的鲁棒性。

著录项

  • 来源
    《Journal of supercomputing》 |2020年第11期|8756-8770|共15页
  • 作者单位

    Zhongkai Univ Agr & Engn Coll Automat 501 Zhongkai Rd Guangzhou Guangdong Peoples R China;

    Guangdong Inst Intelligent Mfg Guangdong Key Lab Modern Control Technol 13 Courtyard 100 Xianlie Rd Guangzhou Guangdong Peoples R China;

    Univ Calif Davis Dept Comp Sci Davis CA 95616 USA;

    Northwestern Polytech Univ Sch Software Xian Peoples R China;

    Dongguan Polytech Dept Comp Engn Dongguan Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Image segmentation; Color disease spot image; Fuzzy C-means; Chaos particle swarm;

    机译:图像分割;颜色疾病斑点图像;模糊C型方式;混沌粒子群;

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