Title :
Unsupervised color texture feature extraction and selection for soccer image segmentation
Author :
Vandenbroucke, Nicolas ; Macaire, Ludovic ; Postaire, Jack-Gérard
Author_Institution :
Lab. d´´Automatique I3D, Univ. des Sci. et Tech. de Lille Flandres Artois, Villeneuve d´´Ascq, France
Abstract :
We describe a new approach for color texture feature extraction and selection. We define color texture features as texture features which are computed by taking into account the color components of the pixels. We determine the most discriminating color texture features among a multidimensional set of color texture features by means of an iterative feature selection procedure associated to an information criterion. This procedure analyses images which are classified by a competitive learning scheme. Soccer image segmentation is achieved by pixel classification. The classification algorithm takes into account these color texture features which are processed in the neighborhood of the pixels. We apply our new unsupervised approach to soccer images segmentation.
Keywords :
feature extraction; image classification; image colour analysis; image segmentation; image texture; iterative methods; unsupervised learning; competitive learning; image classification algorithm; iterative feature selection; multidimensional set; pixel classification; pixel color components; soccer image segmentation; unsupervised color texture feature extraction; unsupervised color texture feature selection; Color; Data mining; Feature extraction; Image analysis; Image segmentation; Iterative algorithms; Pixel; Supervised learning; Unsupervised learning;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC, Canada
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899830