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The HCM for perceptual image segmentation
  • Jonathon Randall, University of Sydney
  • Ling Guan, Ryerson University
  • Wanqing Li, University of Wollongong
  • Xing Zhang, STMicroelectronics R&D
Document Type
Journal Article
Publication Date
This paper presents an application of a neural network, namely the hierarchical cluster model (HCM) to intermediate-level image segmentation. The HCM forms a biological model of the brain for image region segmentation employing Gestalt rules. In particular, a three level HCM is proposed to hierarchically merge pixels into regions and methods are developed to quantify the Gestalt properties of similarity, continuity, closure and co-circularity as merging evidence between regions. Experiments have shown that the proposed algorithm produced more consistent results to manual segmentation than the well-known JSEG method.
Citation Information
Jonathon Randall, Ling Guan, Wanqing Li and Xing Zhang. "The HCM for perceptual image segmentation" Neurocomputing Vol. 71 Iss. 10-12 (2008) p. 1966 - 1979
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