期刊
APPLIED SOFT COMPUTING
卷 13, 期 4, 页码 2017-2036出版社
ELSEVIER
DOI: 10.1016/j.asoc.2012.11.038
关键词
Color image segmentation; Histogram splitting and merging; Fuzzy C-means
资金
- Fundamental Research Grant Scheme (FRGS)
- Ministry of Higher Education (MOHE), Malaysia
- Universiti Sains Malaysia (USM)
This paper presents the Region Splitting and Merging-Fuzzy C-means Hybrid Algorithm (RFHA), an adaptive unsupervised clustering approach for color image segmentation, which is important in image analysis and in understanding pattern recognition and computer vision field. Histogram thresholding technique is applied in the formation of all possible cells, used to split the image into multiple homogeneous regions. The merging technique is applied to merge perceptually close homogeneous regions and obtain better initialization for the Fuzzy C-means clustering approach. Experimental results have demonstrated that the proposed scheme could obtain promising segmentation results, with 12% average improvement in clustering quality and 63% reduction in classification error compared with other existing segmentation approaches. (C) 2012 Elsevier B.V. All rights reserved.
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