*Project Title*
A comparative study of texture descriptors.

*Project Description* 

Texture is a powerful discriminating feature, present almost everywhere in nature. 
Many CBIR systems have been using texture descriptors in their retrieval engine.

This project will involve the following tasks:
* Implementing a set of image descriptors based on texture property;
* Comparing these descriptors in terms of common measures like precision and recall;
* Code documentation.

*Language/technology skills*
C language.

*Number of People*
1-2

*Project Resources*

1.  Co-occurrence matrix

R. M. Haralick, K. Shanmugam and I. Dinstein, Textural Features for Image Classification,
IEEE Transactions on Systems, Man and Cybernatics, 3, 6, 610--621, 1973.

2. Wavelet-based descriptors

B. S. Manjunath and  W. Y. Ma, Texture Features for Browsing and Retrieval of Image Data,
IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 8, 837--842,August, 1996.

3. MPEG-7 texture descriptors

B. S. Manjunath, J. R. Ohm, V. V. Vasudevan and A. Yamada, Color and Texture Descriptors,
IEEE Transactions on Circuits and Systems for Video Technology, 11, 6, 703--715, June, 2001