Region-based binary tree representation for image classification

Author

Wang, Zhiyong ; Feng, Dagan ; Chi, Zheru

Author_Institution

Sch. of Inf. Technol., Sydney Univ., NSW, Australia

Volume

1

fYear

2003

fDate

14-17 Dec. 2003

Firstpage

232

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.

Keywords

image classification; image representation; image segmentation; tree data structures; data structure algorithm; image classification; image segmentation; region merging method; region-based binary tree representation; Australia; Binary trees; Classification tree analysis; Image classification; Image processing; Image retrieval; Image segmentation; Information retrieval; Information technology; Taxonomy;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on

Conference_Location

Nanjing

Print_ISBN

0-7803-7702-8

Type

conf

DOI

10.1109/ICNNSP.2003.1279254

Filename

1279254