Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23656
Title: Image segmentation by clustering of spatial patterns
Authors: Xia, Y
Feng, D
Wang, T
Zhao, R
Zhang, Y
Keywords: Fuzzy clustering
Image segmentation
Image texture analysis
Spatial pattern
Issue Date: 2007
Publisher: Elsevier
Source: Pattern recognition letters, 2007, v. 28, no. 12, p. 1548-1555 How to cite?
Journal: Pattern recognition letters 
Abstract: This letter describes an approach to perceptual segmentation of images through the means of clustering of spatial patterns. An image is modeled as a set of spatial patterns defined on a rectangular lattice. The distance between a spatial pattern and each cluster is defined as a combination of the Euclidean distance in the feature space and the spatial dissimilarity which reflects how much of the pattern's neighbourhood is occupied by other clusters. Our approach has been compared with the Fuzzy C-Mean (FCM) algorithm, a spatial fuzzy clustering algorithm and a Markov Random Field (MRF) based algorithm by segmenting synthetic images, texture mosaics and natural images. The results of those comparative experiments demonstrate that the proposed approach can segment images more effectively and provide more robust segmentation results.
URI: http://hdl.handle.net/10397/23656
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2007.03.012
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