Selecting texture discriminative descriptors of capsule endpscopy images

P. Szczypinski, A. Klepaczko
2009 2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis  
In supervised data classification one of the problems is to reduce dimensionality of feature vectors. It is important to find such features which have high ability for discrimination of diverse classes and to get rid of features which are useless for such discrimination. In this paper we propose a new method for feature subset selection utilizing a convex hull (or convex polytope). The method searches for feature space subspaces in which vectors of one class cluster and they are surrounded by
more » ... ctors of the other class. The method is applied for selection of color and texture descriptors of capsule endoscope images. The study aims at finding a small set of descriptors for detection of pathological changes in the gastrointestinal tract. The results are compared with results produced by a Support Vector Machine with the radial basis function kernel.
doi:10.1109/ispa.2009.5297634 fatcat:ixcp7n47ujf7tavu2rv5mjnx3y