The ball detection in soccer images is one of the applications of the most general problem of object recognition, where the approach mainly used is based on classifying the pattern images after a suitable pre-processing. In this paper we have compared two different pre-processing techniques: the initial vectorial representation of the image has been projected both on the Haar basis and on the basis extracted from the Independent Component Analysis (ICA). The coefficients of the new representation in the ICA and Wavelet subspaces are supplied as input to a neural classifier. ICA and Wavelet representations have been chosen since they are well suited to increase the inter class differences and decrease the intra class ones. The experimental results on real soccer images show that the classification performances applying the ICA and Wavelet pre-processing techniques are quite the same and that combining ICA and Wavelet the percentage of pattern recognition can be further increased.

Keywords: Wavelet Decomposition, Independent Component Analysis, Neural Networks, Feature Selection, Pattern Recognition

	Marco Leo was born in Gallipoli -Lecce- (Italy) in 1974 and he received a degree in Computer Science Engineering from the University of Lecce in 2001. Since then, he is a researcher at the Italian National Research Council (C.N.R.), Institute of Intelligent Systems for Automation (ISSIA) in Bari (Italy). His research interests are in the area of image and signal processing, neural networks and pattern recognition
	Tiziana D'Orazio received the degree in Computer Science from University of Bari in 1988. Since 1989 she is a researcher at the Institute for Signal and Image Processing of the Italian National Research Council (C.N.R.) in Bari (Italy). Her current research interests are in the fields of feature extraction, reinforcement learning, autonomous robots, behavior coordination.
	Paolo Spagnolo was born in Maglie -Lecce- (Italy) in 1975 and he received a degree in Computer Science Engineering from the University of Lecce in 2002. Since then, he is a collaborator of research at the Italian National Research Council (C.N.R.), Institute of Study on Intelligent Systems for Automation (ISSIA) in Bari (Italy). His research interests are in the area of image processing, motion detection and pattern recognition.
	Arcangelo DISTANTE received the degree in Computer Science from the University of Bari (Italy) in 1976. He joined the National Nuclear Physics Institute until 1983 where he worked on various theoretical and computation aspects of 3D reconstruction and pattern recognition of nuclear events. Since 1984 he has been working with the Institute for Signal and Image Processing (IESI) of Italian National Research Council (CNR). Currently he is the coordinator of the Robot Vision Group and the Director of the Institute of Intelligent System for Automation (ISSIA - CNR). In 1996 he joined the University of Lecce where he is associate professor in Theory and Practice of Image Processing at the Faculty of Engineering. His current research deals with computer vision, pattern recognition, machine learning, neural computation, robot navigation and architectures for computer vision. Dr. Arcangelo DISTANTE is a member of IAPR and SPIE.