首页> 外文会议>International Conference on Intelligent Computing and Integrated Systems >Method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm
【24h】

Method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm

机译:基于模糊C-均值聚类算法和人工鱼群算法的图像分割方法

获取原文

摘要

By analyzing advantages and disadvantages of Fuzzy C-Means Clustering Algorithm, a method of image segmentation based on Fuzzy C-Means Clustering Algorithm and Artificial Fish Swarm Algorithm is proposed. The image is segmented in terms of the values of the membership of pixels, Artificial Fish Swarm Algorithm is introduced into Fuzzy C-Means Clustering Algorithm, and through the behavior of prey, follow, swarm of artificial fish, the optimised clustering center could be selected adaptively, then the values of the membership of pixels available with Fuzzy C-Means Clustering Algorithm, and the image segmentation is completed. The experimental results show the effectiveness and feasibility.
机译:通过分析模糊C均值聚类算法的优缺点,提出了一种基于模糊C均值聚类算法和人工鱼群算法的图像分割方法。根据像素的隶属度值对图像进行分割,将人工鱼群算法引入到模糊C均值聚类算法中,通过猎物的行为,跟随,人工鱼群的选择,可以选择最优的聚类中心自适应地,然后使用模糊C均值聚类算法获得可用的像素隶属度值,并完成图像分割。实验结果表明了该方法的有效性和可行性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号