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A novel self-organizing neural network called the evolving tree is applied to classification of defect images. The evolving tree resembles the self-organizing map (SOM) but it has several advantages over the SOM. Experiments present a comparison between a normal SOM, a supervised SOM, and the evolving tree algorithm for classification of defect images that are taken from a real web inspection system. The MPEG-7 standard feature descriptors are applied. The results show that the evolving tree provides better classification accuracies and reduced computational costs over the normal SOMs.
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on (Volume:4 )
Date of Conference: 25-29 July 2004