Title :
Texture classification based on contourlet and support vector machines
Author_Institution :
Coll. of Math., Phys. & Inf. Eng., Zhejiang Normal Univ., Jinhua, China
Abstract :
We propose an texture classification method for the image classification of objects in 2D images. The algorithm is based on recent developments in support vector machines and contourlet transform. The texture classification method is robust in the presence of noise. The method has been implemented and performed experiments on some image data. Our experimental results showed characteristics of our method. In the end, the future research directions are discussed.
Keywords :
image classification; image texture; support vector machines; transforms; 2D images; contourlet transform; image classification; support vector machines; texture classification; Computational complexity; Feature extraction; Filter bank; Gabor filters; Image classification; Signal processing; Statistical analysis; Support vector machine classification; Support vector machines; Wavelet transforms; Contourlet; SVM; Texture Classification;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5267510
