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Proceedings Paper

Image classification by classifier combining technique
Author(s): Ke Liu; Yea-Shuan Huang; Ching Y. Suen
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Paper Abstract

A classification method has been proposed to recognize images of multiple classes based on algebraic feature extraction and classifier combining techniques. First, an image algebraic feature extraction method is applied to all pairs of classes to extract the image features. Then, a nearest neighbor classifier with a small number of prototypes is designed for each pair of classes based on the algebraic features of training samples. Finally, a neural network technique is used to combine the measurement values of paired classes. Experiments on the U.S. zip code data base show that the method is effective.

Paper Details

Date Published: 30 June 1994
PDF: 8 pages
Proc. SPIE 2304, Neural and Stochastic Methods in Image and Signal Processing III, (30 June 1994); doi: 10.1117/12.179229
Show Author Affiliations
Ke Liu, Concordia Univ. (Canada)
Nanjing Univ. of Science and Engineering (China)
Yea-Shuan Huang, Concordia Univ. (Canada)
Industrial Technology Research Institute (Taiwan)
Ching Y. Suen, Industrial Technology Research Institute (Taiwan)


Published in SPIE Proceedings Vol. 2304:
Neural and Stochastic Methods in Image and Signal Processing III
Su-Shing Chen, Editor(s)

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