Rotation Invariant Image Classification Based on MPEG-7 Homogeneous Texture Descriptor

Authors:
Lei Zhang;Jun Ma;Xinshun Xu;Bo Yuan
Affiliations:
Shandong University, China;Shandong University, China;Shandong University, China;University of Southern California, Los Angeles, USA
Venue:
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03
Year:
2007

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Abstract

Image classification based on texture features plays an important role in content-based image retrieval. A novel method for rotation invariant image classification is proposed based on MPEG-7 Homogeneous Texture Descriptor (HTD). To compute HTD, Gabor transform is first performed by filtering image using a bank of orientation and scale selective band-pass filters called Gabor wavelets. For constructing the feature vector, the mean energy and standard deviation are calculated separately on each filtered and original image. Then the summations of energy in different direction are calculated and the direction with the maximum energy is chosen as the dominant orientation, which is used to shift the feature vector circularly in order to keep rotation invariant. The classification is done by SVM (Support Vector Machine). The method is tested on Brodatz and UIUCTex datasets. The experiments demonstrate the method is effective and efficient for rotation invariant texture classification.