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Volume: 4 | Article ID: art00069
Neighborhood and Haralick feature extraction for color texture analysis
  DOI :  10.2352/CGIV.2008.4.1.art00069  Published OnlineJanuary 2008

In this paper, we propose to study the influence of the neighborhood used to process the color co-occurrence matrices on the quality of texture analysis.First, we measure the discriminating power of Haralick features extracted from the color co-occurrence matrices of color images coded in 28 different color spaces, and we select the most discriminating one for different 3x3 neighborhoods. Then, we experimentally verify that the most discriminating feature space, built by using an iterative selection procedure, depends on the chosen neighborhood and finally we study the impact of the neighborhood choice on the classification results by using the same feature space but different neighborhoods.Experimental results achieved with the Barktek database have firstly shown the adequacy between the discriminating power of the selected feature space and the rate of well-classified images. We have also seen that the choice of the neighborhood does not highly influence the selection of the most discriminating feature but has a significant impact on the quality of discrimination between the considered textures. Indeed, we have worked with textures which contain vertical patterns and have shown that the best classification results have been obtained with horizontal neighborhoods. The choice of the neighborhood depends consequently on the analysed textures.

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A. Porebski, N. Vandenbroucke, L. Macaire, "Neighborhood and Haralick feature extraction for color texture analysisin Proc. IS&T CGIV 2008/MCS'08 4th European Conf. on Colour in Graphics, Imaging, and Vision 10th Int'l Symp. on Multispectral Colour Science,  2008,  pp 316 - 321,

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