Color image segmentation based on homogram thresholding and region merging
Color image segmentation based on homogram thresholding and region merging
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DOI：
10.1016/s0031-3203(01)00054-1
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发表时间：
2002-02-01
影响因子：
8
通讯作者：
Wang, JL
中科院分区：
文献类型：
--
作者：
Cheng, HD;Jiang, XH;Wang, JL
提出了一种基于单应图阈值分割和区域合并的彩色图像分割方法。单应图既考虑了灰度级的出现，又考虑了像素之间的相邻均匀性值。因此，它使用本地和全局信息。利用模糊熵作为一种工具来执行homogram分析，在第一阶段找到所有主要的同质区域。然后根据颜色相似性进行区域合并，避免过分割。提出的基于单应图的方法（HOB）与基于直方图的方法（HIB）进行了比较。实验结果表明，HOB算法比HIB算法能更有效地发现均匀区域，并在一定程度上解决了彩色图像中阴影的判别问题。(C)2001年模式识别学会。由爱思唯尔科技有限公司出版。保留所有权利。
In this paper, a color image segmentation approach based on homogram thresholding and region merging is presented. The homogram considers both the occurrence of the gray levels and the neighboring homogeneity value among pixels. Therefore, it employs both the local and global information. Fuzzy entropy is utilized as a tool to perform homogram analysis for finding all major homogeneous regions at the first stage. Then region merging process is carried out based on color similarity among these regions to avoid oversegmentation. The proposed homogram-based approach (HOB) is compared with the histogram-based approach (HIB). The experimental results demonstrate that the HOB can find homogeneous regions more effectively than HIB does, and can solve the problem of discriminating shading in color images to some extent. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.