Scene classification using adaptive processing of tree representation of rectangular-shape partition of images

Authors:
Wei Sun;Ken Lo;Zheru Chi
Affiliations:
Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China;Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China;Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

Image classification is very helpful for organizing large image databases and content based image retrieval (CBIR). However, it is very complex and challenging because of lacking effective methods. In this paper, we present a tree representation of images based on rectangular-shape partition. Then an adaptive processing algorithm is adopted to perform the classification task. Experimental results on seven categories of scenery images show that the structural representations are better than the traditional methods and our previous work based on quadtree representation of fixed partition.