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Journal of Electronic Imaging

Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks
Author(s): Zheng Jason Geng; Weicheng Shen
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Paper Abstract

We present some preliminary study results of an automated fingerprint pattern classification approach based on a novel neural network structure called the fuzzy cerebellar model arithmetic computer (CMAC) neural network. The fingerprint images are first preprocessed to generate ridge flow, then the Karhunen-Loever (K-L) transform is used to extract the features from the ridge-flow images. The feature vector is then sent to a fuzzy CMAC neural network for classification. Excellent results were obtained through our preliminary experiments on the "two classes" problem.

Paper Details

Date Published: 1 July 1997
PDF: 8 pages
J. Electron. Imaging. 6(3) doi: 10.1117/12.269896
Published in: Journal of Electronic Imaging Volume 6, Issue 3
Show Author Affiliations
Zheng Jason Geng, Genex Technologies, Inc. (United States)
Weicheng Shen, Infotec Development Inc. (United States)


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