Abstract
Most existing minutiae extraction methods require image preprocessing 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). © Springer-Verlag Berlin Heidelberg 2004.
Cite
CITATION STYLE
Wahab, A., Tan, E. C., & Jonatan, A. (2004). Direct gray-scale minutiae extraction. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3072, 280–286. https://doi.org/10.1007/978-3-540-25948-0_39
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