Abstract
Most existing minutiae extraction methods require image pre-processing which has certain drawbacks. Direct gray-scale minutiae extraction approaches that work on the original image is thus preferred. The use of fuzzy neural network (FNN) as a recognition system to detect the minutiae pattern has been shown to be promising and several types of FNNs have been proposed. Here, we propose a new approach to perform direct gray-scale minutiae extraction based on a more powerful generic self-organizing FNN (GenSoFNN).
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Wahab, A., Tan, E.C., Jonatan, A. (2004). Direct Gray-Scale Minutiae Extraction. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_39
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DOI: https://doi.org/10.1007/978-3-540-25948-0_39
Publisher Name: Springer, Berlin, Heidelberg
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