Abstract In this paper, a Zernike moments"based descriptor i s used as a measure of shape information for the de tection of buildings from Very High Spatial Resolution (VHSR) satellite images. The proposed approach comprises three steps. First, the image is segmented into homogeneous objects based o n the spectral and spatial information. MeanShift segmentation method is used for this end. Second, a Zernike feature vec tor is computed for each segment. Finally, a Suppor t Vector Machines (SVM)"based classification using the feature vector s as inputs is performed. Experimental results and comparison with Environment for Visualizing Images (ENVI) commercial package confirm the effectiveness of the proposed approach.

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[28] Zhang D. and Lu G., Content Retrieval using Different Shape Descriptors Comparative Study, in Proceedings of International Conference on Multimedia and Expo , Japan, pp. 3170320, 2001. Habib Mahi Engineering degree science from the University of Mohamed Boudiaf 1994 and MS degree in Techniques Spatiales et Applications Centre of Space Techniques Algeria, in 2004. During 2004, he is a permanent researcher at the Earth Observation Division of CTS His research interests include: image processing, feature extraction, classification development for remotely sensed data. Hadria Isabaten Engineering degree i Engineering from the University of Mohamed Boudiaf Docteur Ing nieur industrial computer science automation from the University of Lille 1 in France, in 1987 and the computer science from the University of Mohamed Boudiaf in 2005. Currently she is a Faculty of Computer Science in the Mohamed Boudiaf. Her research interests cover image processing and the application of pattern recogniti on to remotely sensed data. Zernike Moments and SVM for Shape Classification in Very High Resolution Satellite Images IEEE Transaction on vol. 7, no. 3, pp. , A Combined Based Approach High Resolution Multispectral Data Over Urban Areas, IEEE Geoscience and Remote Sensing, 2003. via the General ournal of the Optical . 8, pp. 9200930, Image Analysis by the IEEE Transaction on Analysis and Machine Intelligence, vol. Learning Theory, Wiley, Zhang D. and Lu G., Review of Shape Description Techniques, no. 1, pp. 1019, and Lu G., Content0Based Shape Different Shape Descriptors: A in Proceedings of IEEE International Conference on Multimedia and received his degree in computer the University of in Algeria, in degree in Techniques Spatiales et Applications from the Centre of Space Techniques in he is a permanent researcher at the Earth Observation Division of CTS. research interests include: image processing, image feature extraction, classification algorithms . Isabaten received her degree in Electrical Engineering from the University of Mohamed Boudiaf in 1981, the Docteur Ing nieur degree in industrial computer science and from the University of and the phD degree in from the University of Mohamed a professor in the in the University of Her research interests cover image processing and the application of pattern recogniti on to Chahira Serief Engineer in Electrical University of Constantine in Algeria, respectively been working as a permanent researcher at the Earth Observation Division of the Centre of Space Techniques in Algeria. Her principal research interests are in the fields of satellite and medical image processing, image feature extraction; image registration, image segmentation and contour detection. 51 Chahira Serief received her Engineering, Ms, and PhD degrees in Electrical Engineering from the University of Constantine in , in 1995, 2000, and 2009 respectively. Since 2002 she has been working as a permanent researcher at the Earth Observation Division of the Centre of Space Techniques in Algeria. Her principal ch interests are in the fields of satellite and medical image processing, image feature extraction; image registration, image segmentation and contour