1 July 1997 Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks
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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, Zheng Jason Geng, Weicheng Shen, 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 . Submission:
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