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CTex - an adaptive unsupervised segmentation algorithm based on color-texture coherence

Ilea, Dana E. and Whelan, Paul F. (2008) CTex - an adaptive unsupervised segmentation algorithm based on color-texture coherence. IEEE Transactions on Image Processing, 17 (10). pp. 1926-1939. ISSN 1057-7149

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This paper presents the development of an unsupervised image segmentation framework (referred to as CTex) that is based on the adaptive inclusion of color and texture in the process of data partition. An important contribution of this work consists of a new formulation for the extraction of color features that evaluates the input image in a multispace color representation. To achieve this, we have used the opponent characteristics of the RGB and YIQ color spaces where the key component was the inclusion of the self organizing map (SOM) network in the computation of the dominant colors and estimation of the optimal number of clusters in the image. The texture features are computed using a multichannel texture decomposition scheme based on Gabor filtering. The major contribution of this work resides in the adaptive integration of the color and texture features in a compound mathematical descriptor with the aim of identifying the homogenous regions in the image. This integration is performed by a novel adaptive clustering algorithm that enforces the spatial continuity during the data assignment process. A comprehensive qualitative and quantitative performance evaluation has been carried out and the experimental results indicate that the proposed technique is accurate in capturing the color and texture characteristics when applied to complex natural images.

Item Type:Article (Published)
Uncontrolled Keywords:image analysis; Adaptive Spatial K-Means clustering; colourtexture segmentation; multi-channel texture decomposition; multi-space colour segmentation; SOM classification;
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:
Copyright Information:©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:4677
Deposited On:07 Jul 2009 11:11 by DORAS Administrator. Last Modified 27 Oct 2017 10:22

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