Colour Image Segmentation Using Homogeneity Method and Data Fusion Techniques. (16th June 2009)

• Record Type: Journal Article
• Authors: Ben Chaabane Ben Chaabane, Salim Salim; Sayadi Sayadi, Mounir Mounir; Fnaiech Fnaiech, Farhat Farhat; Brassart Brassart, Eric Eric
• Other Names: Tavares Tavares João Manuel R. S. João Manuel R. S. Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2009-06-16
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/367297
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : A novel method of colour image segmentation based on fuzzy homogeneity and data fusion techniques is presented. The general idea of mass function estimation in the Dempster-Shafer evidence theory of the histogram is extended to the homogeneity domain. The fuzzy homogeneity vector is used to determine the fuzzy region in each primitive colour, whereas, the evidence theory is employed to merge different data sources in order to increase the quality of the information and to obtain an optimal segmented image. Segmentation results from the proposed method are validated and the classification accuracy for the test data available is evaluated, and then a comparative study versus existing techniques is presented. The experimental results demonstrate the superiority of introducing the fuzzy homogeneity method in evidence theory for image segmentation.