首页> 外文会议>2014 12th International Conference on Signal Processing >Image segmentation based on 2D Renyi gray entropy and Fuzzy Clustering
【24h】

Image segmentation based on 2D Renyi gray entropy and Fuzzy Clustering

机译:基于二维Renyi灰度熵和模糊聚类的图像分割

获取原文
获取外文期刊封面目录资料

摘要

Because of the high calculating complexity of classical two-dimensional Renyi entropy thresholding, an improved algorithm is proposed in the paper. Instead of calculating the traditional 2D Renyi threshold, it reduced the complexity by computing two 1D Renyi threshold. In order to improve the global segmentation performance, we adopted FCM (Fuzzy C-means Clustering) to the algorithm. Experimental results showed that this improved algorithm gave full play to the advantages of both, validating the effectiveness of improved algorithm.
机译:由于经典二维Renyi熵阈值算法的计算复杂度高,提出了一种改进的算法。它无需计算传统的2D Renyi阈值,而是通过计算两个1D Renyi阈值来降低复杂度。为了提高全局分割性能,我们对算法采用了FCM(模糊C均值聚类)。实验结果表明,该改进算法充分发挥了两者的优势,验证了改进算法的有效性。

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