Title :
A new wavelet based ART network for texture classification
Author :
Wang, J. ; Naghdy, G. ; Ogunbona, P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Wollongong Univ., NSW, Australia
Abstract :
A new method for texture classification is proposed. It is composed of two processing stages, namely, a low level evolutionary feature extraction based on Gabor wavelets and a high level neural network based pattern recognition. This resembles the process involved in the human visual system. Gabor wavelets are exploited as the feature extractor. A neural network, fuzzy adaptive resonance theory (fuzzy ART), acts as the high level decision making and recognition system. Some modifications to the fuzzy ART make it capable of simulating the post-natal and evolutionary development of the human visual system. The proposed system has been evaluated using natural textures. The results obtained show that it is able to effectively perform the object recognition task and will find useful application in the study of the human visual system model for artificial vision
Keywords :
ART neural nets; computer vision; feature extraction; fuzzy neural nets; image classification; image texture; object recognition; pattern recognition; wavelet transforms; Gabor wavelets; artificial vision; evolutionary development; fuzzy adaptive resonance theory neural network; high level decision making; high level neural network; human visual system; low level evolutionary feature extraction; natural textures; object recognition; pattern recognition; texture classification; wavelet based ART network; Adaptive systems; Feature extraction; Fuzzy neural networks; Fuzzy systems; Humans; Neural networks; Pattern recognition; Resonance; Subspace constraints; Visual system;
Conference_Titel :
Intelligent Information Systems, 1996., Australian and New Zealand Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-3667-4
DOI :
10.1109/ANZIIS.1996.573948
