Share Email Print
cover

Proceedings Paper

Using opponent correlation functions to recognize color texture
Author(s): Mohammed Al-Rawi; Jie Yang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We propose a new approach to model texture in 2D color images based on opponent correlation functions computed within and between sensor bands of a red-green-blue image. The new opponent correlations cover all the possible opponent autocorrelations and opponent crosscorrelations of a color image. Invariants of opponent correlations are computed with the aid of Zernike moments to preserve rotation, translation, and scale invariance. The method can be used in the classification (even with slight illumination changes) and the unsupervised segmentation of color texture in a variety of image processing and pattern recognition tasks. One of the most important points in introducing the opponent correlation functions is the efficient computation compared to the direct spatial correlation method that requires heavy computations.

Paper Details

Date Published: 21 September 2001
PDF: 6 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441465
Show Author Affiliations
Mohammed Al-Rawi, Shanghai Jiaotong Univ. (China)
Jie Yang, Shanghai Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition

© SPIE. Terms of Use
Back to Top