Title :
Watershed-based textural image segmentation
Author :
Wang, Shuang ; Ma, Xiuli ; Zhang, Xiangrong ; Jiao, Licheng
Author_Institution :
Xidian Univ., Xian
fDate :
Nov. 28 2007-Dec. 1 2007
Abstract :
The watershed transform is a well-established tool for image segmentation. However, watershed segmentation is often not effective for textural images. In this paper, we describe an improved watershed segmentation algorithm combined with texture features. The aim of this study is to improve the generalization of watershed techniques and to construct a well segmentation of textural images. The method includes two stages. The first stage is standard watershed algorithm. The second stage is processed by a clustering algorithm, fuzzy c-means (FCM). Watershed algorithm provides small homogenous patches which are merged by clustering algorithm based on texture features. The experimental results demonstrate that the combined algorithm is effective for textural image segmentation.
Keywords :
feature extraction; fuzzy set theory; image segmentation; image texture; pattern clustering; clustering algorithm; fuzzy c-means; texture features; watershed transform; watershed-based textural image segmentation; Clustering algorithms; Filtering algorithms; Image processing; Image segmentation; Information processing; Merging; Object recognition; Pixel; Signal processing; Signal processing algorithms; image segmentation; texture; watershed;
Conference_Titel :
Intelligent Signal Processing and Communication Systems, 2007. ISPACS 2007. International Symposium on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-1447-5
Electronic_ISBN :
978-1-4244-1447-5
DOI :
10.1109/ISPACS.2007.4445886