1 July 1997 Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks
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J. of Electronic Imaging, 6(3), (1997). doi:10.1117/12.269896
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.
Zheng Jason Geng, Weicheng Shen, "Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks," Journal of Electronic Imaging 6(3), (1 July 1997). https://doi.org/10.1117/12.269896
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