By Topic

Texture classification using rotated wavelet filters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sam-Deuk Kim ; Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA ; S. Udpa

We propose an approach to the texture classification problem using a set of two-dimensional (2-D) wavelet filters that are nonseparable and oriented for improved characterization of diagonally oriented textures. Channel energies are estimated at the output of both the new filter bank and a standard discrete wavelet frames (DWF) filter bank. Classification results obtained using each individual method and in combination are presented. The results show that the oriented filter set results in finer discrimination providing complementary texture information to the DWF by making use of its orientation selectivity. As a result, a combination of the features from the output of two filter banks improved the classification accuracy significantly with a smaller number of features

Published in:

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans  (Volume:30 ,  Issue: 6 )