The HCM for perceptual image segmentation

Authors:
Jonathan Randall;Ling Guan;Wanqing Li;Xing Zhang
Affiliations:
The University of Sydney, NSW 2006, Australia;Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada M5B 2K3;SCSSE, University of Wollongong, Australia;STMicroelectronics R&D (Shanghai) Co. Ltd., China
Venue:
Neurocomputing
Year:
2008

Citing 18
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Abstract

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.