Paper Info
Title
CTex--an adaptive unsupervised segmentation algorithm based on color-texture coherence.
Abstract
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.
Year
DOI
Venue
2008
10.1109/TIP.2008.2001047
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Keywords
Field
DocType
gabor filter,image representation,pattern clustering,color-texture coherence,mathematical descriptor,multichannel texture decomposition,som classification,image segmentation,multichannel texture decomposition scheme,gabor filters,self organizing map network,feature extraction,multispace color segmentation,adaptive clustering algorithm,color-texture segmentation,adaptive unsupervised segmentation algorithm,multispace color representation,self-organising feature maps,image texture,adaptive spatial k-means clustering,image colour analysis
k-means clustering,Computer vision,Color space,Pattern recognition,Image texture,Image segmentation,Artificial intelligence,RGB color model,Adaptive algorithm,Mathematics,Texture filtering,Color image
Journal
Volume
Issue
ISSN
17
10
1057-7149
Citations 
PageRank 
References 
49
1.57
32
Authors
2
Name
Order
Citations
PageRank
Dana E Ilea1501.92
Paul F. Whelan256139.95