File(s) not publicly available

A texture feature extraction technique using 2D-DFT and hamming distance

conference contribution
posted on 06.12.2017, 00:00 authored by Y Tao, V Muthukkumarasamy, M Blumenstein, Brijesh VermaBrijesh Verma
Texture analysis plays an increasingly important role in computer vision. Since the textural properties of images appear to carry useful information for discrimination purposes, it is important to develop significant features for texture. This paper presents a novel technique for texture extraction and classification. The proposed feature extraction technique uses 2D–DFT transformation. A combination of this technique and a Hamming Distance based neural network for classification of extracted features is investigated. The experimental results on a benchmark database and detailed analysis are presented.

History

Start Page

120

End Page

125

Number of Pages

6

Start Date

01/01/2003

Finish Date

01/01/2003

ISBN-10

0769519571

Location

Xi'an, Shaanxi Sheng, China

Publisher

IEEE Computer Society

Place of Publication

United States

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Griffith University;

Era Eligible

Yes

Name of Conference

International Conference on Computational Intelligence and Multimedia Applications