Can I read A Statistical Approach to Texture Classification from Single Images on EtoBox?

A Statistical Approach to Texture Classification from Single Images by Manik Varma; Andrew Zisserman is a Computer Science article available to read on EtoBox.

What is A Statistical Approach to Texture Classification from Single Images about?

We investigate texture classification from single images obtained under unknown viewpoint and illumination. A statistical approach is developed where textures are modelled by the joint probability distribution of filter responses. This distribution is represented by the frequency histogram of filter response cluster centres (textons). Recognition proceeds from single, uncalibrated images and the novelty here is that rotationally invariant filters are used and the filter response space is low dimensional. Classification performance is compared with the filter banks and methods of Leung and Malik [IJCV, 2001], Schmid [CVPR, 2001] and Cula and Dana [IJCV, 2004] and it is demonstrated that superior performance is achieved here. Classification results are presented for all 61 materials in the Columbia-Utrecht texture database. We also discuss the effects of various parameters on our classification algorithm-such as the choice of filter bank and rotational invariance, the size of the texton dictionary as well as the number of training images used. Finally, we present a method of reliably measuring relative orientation co-occurrence statistics in a rotationally invariant manner, and discu

Who reads A Statistical Approach to Texture Classification from Single Images?

Author

Manik Varma; Andrew Zisserman

Publisher

Springer Science and Business Media LLC

Published

2005

Language

EN

Field

Computer Science (Physical Sciences)