首页> 外文期刊>Journal of Computers >A Fast Image Thresholding Method Based on Chaos Optimization and Recursive Algorithm for Two- Dimensional Tsallis Entropy
【24h】

A Fast Image Thresholding Method Based on Chaos Optimization and Recursive Algorithm for Two- Dimensional Tsallis Entropy

机译:一种基于混沌优化和递归算法的快速图像阈值算法二维Tsallis熵

获取原文
           

摘要

—The two-dimensional (2-D) maximum Tsallis entropy method often gets ideal segmentation results, because it not only takes advantage of the spatial neighbor information with using the 2-D histogram of the image, but also has some flexibility with a parameter. However, its time-consuming computation is often an obstacle in real time application systems. In this paper, a fast image thresholding method based on chaos optimization and recursive algorithm for 2-D Tsallis entropy is presented. Firstly, improve the traditional chaos optimization algorithm(COA) so that it can get global solution with lower computation load, then propose a recursive algorithm with the stored matrix variables, finally combine the improved COA and the recursive algorithm to reduce much computational cost in the process of solving the 2-D maximum Tsallis entropy problem. Experimental results show the proposed approach can get better segmentation performance and has much faster speed.
机译:- 二维(2-D)最大TSAllis熵方法经常获得理想的分段结果,因为它不仅利用了使用图像的2-D直方图的空间邻居信息,而且还具有与参数的一些灵活性。然而,其耗时的计算通常是实时应用系统中的障碍。本文提出了一种基于混沌优化和递归算法的快速图像阈值算法,介绍了2-D Tsallis熵的递归算法。首先,提高传统混沌优化算法(COA),使其可以获得具有较低计算负载的全局解决方案,然后提出使用存储的矩阵变量的递归算法,最终将改进的COA和递归算法结合在一起,减少了大量的计算成本解决二维最大Tsallis熵问题的过程。实验结果表明,所提出的方法可以获得更好的分割性能并具有更快的速度。

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