Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37724
Title: Region-based binary tree representation for image classification
Authors: Wang, Z
Feng, D
Chi, Z 
Keywords: Image classification
Image representation
Image segmentation
Tree data structures
Issue Date: 2003
Source: Proceedings of the International Conference on Neural Networks and Signal Processing (ICNNSP'2003), Nanjing, China, 14-17 Dec. 2003, p. 232-235 How to cite?
Abstract: Image classification is a very challenging problem due to lack of effective representations. In this paper, a region-based binary tree representation incorporating with adaptive processing of data structures is proposed to address this problem. After an image is segmented, a binary tree is established to characterize its contents by using region merging method. Finally, an adaptive processing of data structure algorithm is employed to perform the classification task with binary tree representation. Experimental results on seven categories of scenery images show this region-based structural representation is superior to our previous work based on quadtree representation.
URI: http://hdl.handle.net/10397/37724
ISBN: 0-7803-7702-8
ISSN: 1098-7576
DOI: 10.1109/ICNNSP.2003.1279254
Appears in Collections:Conference Paper

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