Hybrid Color-Texture Space for Image Classification

Authors: Hassan El Maia, Ahmed Hammouch, Driss Aboutajdine

Abstract:

This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.

Keywords: Color, texture, laws filter, mutual information, SVM, hybrid space.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070673

References:

[1] M. Mirmehdi and M. Petrou, "Segmentation of Color Textures", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 22, 2, 2000, pp.142-159.
[2] A. Dimbarean, and P. Whelan, "Experiments in color texture analysis", Pattern. Recognition Letters. Vol. 22, 2001. p.1161.
[3] A. Safia, M . F .Belbachir,and T. Iftene. 2006. "La Transformation en ondelettes pour l-extraction de la texture-couleur,Application la classification combine des images (HRV) de SPOT". International journal of remote sensing, Vol. 27, No 18, 20 September, pp. 3977-3990
[4] N. Vandenbroucke, L. Macaire and J. G. Postaire, "Color image segmentation by pixel classification in an adapted hybrid color space. application to soccer image analysis," Computer Vision and Image Understanding, vol. 90, pp. 190-216, 2003.
[5] F. Cointault,D. Gurin,J. P. Guillemin,B. Chopinet. 2008. "In-Field Wheat ears Counting Using Color-Texture Image Analysis", New Zealand Journal of Crop and Horticultural Science, 2008, Vol. 36: 117-130, June 2008.
[6] F. Cointault, B. Chopinet," Colour-texture image analysis for in-field wheat head counting", ISCCSP 2006, Marrakech Morocco.
[7] H. El Maia H, A .Hammouch , D .Aboutajdine, "Hybridization of the color information with the texture by using the mutual information for the classification of satellite images", ICMCS 2009, Ouarzazat Morocco.
[8] A. Kraskov, H. Stogbauer, P. Grassberger, "Estimating mutual information", Physical Review E 69 (2004) 066138.
[9] F. Rossi, D. Franois, V. Wertz, M. Meurens and M. Verleysen. "Fast Selection of Spectral Variables with B-Spline Compression". Chemometrics and Intelligent Laboratory Systems, volume 86, numro 2, pages 208-218. April 2007.
[10] A. Hammouch,D. Aboutajdine and J.M.Boucher, "Evaluation comparative en cartographie forestire de l-analyse de texture et de la transforme en paquets d-ondelettes par le moyen d-un classifieur neuronal", Revue Photo-interprtation, N 2004/1, 2004.
[11] C. Rosenberger, "Conception of an adaptative image segmentation system", Thse de Doctorat de l- Universit de Rennes 1, dcembre 1999.
[12] A. Hammouch, "Apport comparatif en cartographie forestire de l-analyse spatiale de la texture et de la transforme en paquets d-ondelettes", Doctorat d-Etat, FS, Universit Mohammed V-Agdal, Rabat, dcembre 2004.
[13] K. I. Laws, "Texture image segmentation", Ph. D. Thesis, University of Southern California, 1980.
[14] D. Scott, "Multivariable Density Estimation", Theory, Practice, and Visualization, Wiley, New-York, 1992.
[15] V. Vapnik,"Estimation of Dependencies Based on Data" (Springer- Verlag, Trans.). Moscow: Nauka. 1979.
[16] V. Vapnik, "The Nature of Statistical Learning Theory", Berlin:Springer- Verlag 1995.
[17] V. Vapnik, "Statistical Learning Theory", Wiley, New York (1998).
[18] C. W. Hsu and C. J. Lin, " A comparaison of methods for multiclass support vector machines", IEEE Transaction on Neural Network vol.13 pp.415-425, 2002
[19] http://www.csie.ntu.edu.tw/cjlin/libsvm.