Share Email Print

Journal of Electronic Imaging

Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks
Author(s): Zheng Jason Geng; Weicheng Shen
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top