Fabric Texture Classification Based on Wavelet Packet

Author

Shuguang, Liu ; Pingge, Qu

Author_Institution

Xi´´an Polytech. Univ., Xi´´an

fYear

2007

Firstpage

13912

Lastpage

15008

Abstract

The main energy of texture image is concentrated on middle frequency regain, but ordinary image on low frequency regain. With increasing the resolution level, wavelet transform focuses on low frequency domain, but wavelet packet on any frequency domain. Therefore it is very effective to use wavelet packet algorithm to classify the fabric texture. In this study, we use wavelet packet and BP neural network together to classify the fabric texture. Experimental result shows that the classification rate can attain 98%.

Keywords

backpropagation; fabrics; frequency-domain analysis; image classification; image resolution; image texture; neural nets; wavelet transforms; BP neural network; backpropagation; fabric texture classification; frequency domain; image classification; image resolution; texture image; wavelet packet algorithm; wavelet transform; Energy resolution; Fabrics; Fourier transforms; Frequency domain analysis; Frequency measurement; Instruments; Time frequency analysis; Wavelet domain; Wavelet packets; Wavelet transforms; BP neural network; Wavelet packet; fabric; texture classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-1136-8

Electronic_ISBN

978-1-4244-1136-8

Type

conf

DOI

10.1109/ICEMI.2007.4350696

Filename

4350696