Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Contender's network, a new competitive-learning scheme
Pattern Recognition Letters
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data equalisation with evidence combination for pattern recognition
Pattern Recognition Letters
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Minutiae Detection In Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks - 2005 Special issue: IJCNN 2005
An ART-based fuzzy adaptive learning control network
IEEE Transactions on Fuzzy Systems
GenSoFNN: a generic self-organizing fuzzy neural network
IEEE Transactions on Neural Networks
Driving profile modeling and recognition based on soft computing approach
IEEE Transactions on Neural Networks
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Among various biometric verification systems, fingerprint verification is one of the most reliable and widely accepted. One essential part of fingerprint verification is the minutiae extraction system. Most existing minutiae extraction methods require image preprocessing or post processing resulting in additional complex computation and time. Hence, direct gray-scale minutiae extraction approach on the image is preferred. One of these approaches is the use of Fuzzy Neural Network (FNN) as a recognition system to detect the presence of minutiae pattern. Currently, the development of FNN as a tool of recognition has shown a promising prospect. Some researchers have proposed several types of FNN. In particular, a Generic Self Organizing Fuzzy Neural Network (GENSOFNN) has been shown to excel in comparison with other FNN. Therefore, a new approach to perform direct gray-scale minutiae extraction based on GENSOFNN is proposed in this paper. Experimental results show the potential of using GENSOFNN for real-time point of sale (POS) terminal for verification.