標題: Cellular neural networks and PCA neural networks based rotation/scale invariant texture classification
作者: Lin, CT
Chen, SA
Huang, CH
Chung, JF
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: rotation scale invariant;texture classification;cellular neural networks;Gabor-type filtering;principle component analysis neural networks
公開日期: 2004
摘要: In this paper, we proposed a new index which can be used to classify the texture image. Because of the adjustment of image capture device or the distortion of image capture, the texture image may be transformed. Usually those transformations included rotation and scale. The proposed method provides an algorithm to avoid those effects respectively. This approach is the combination of Cellular Neural Networks and Principle Component Analysis Neural Networks. This fact implies it is a feed-forward neural networks, and it does not need any training set.
URI: http://hdl.handle.net/11536/18204
ISBN: 0-7803-8359-1
ISSN: 1098-7576
期刊: 2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS
起始頁: 153
結束頁: 158
顯示於類別:會議論文