Content based texture image classification

Author

Shang, Xiao-qing ; Song, Guo-xiang ; Hou, Biao

Author_Institution

Coll. of Sci., Xidian Univ., Xi´´an, China

Volume

3

fYear

2003

fDate

2-5 Nov. 2003

Firstpage

1309

Abstract

An image can be regarded as a combination of different texture areas. Texture is usually defined as a certain local feature, or it measures the relation between pixels in a local area. It is also an important feature in content based image retrieval. Based on moment feature, a new method for content based texture image classification is proposed using support vector machine and directional information of the image, which combines the characteristics of Brushlet and wavelet transform. Experiments show our method is practicable and effective.

Keywords

content-based retrieval; image classification; image segmentation; image texture; support vector machines; wavelet transforms; Brushlet transform; anisotropic information; content based texture image classification; image retrieval; image segmentation; support vector machine; texture areas; wavelet transform; Educational institutions; Filter bank; Frequency; Image classification; Image texture analysis; Polynomials; Support vector machine classification; Support vector machines; Wavelet packets; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2003 International Conference on

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/ICMLC.2003.1259693

Filename

1259693