Fingerprinting classification using fuzzy cerebellar model arithmetic computer neural networks
Weicheng Shen · Journal of Electronic Imaging · 1997
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.