Uncertainty principles and signal recovery
SIAM Journal on Applied Mathematics
Smoothing Algorithm Based on Multi-Scale Morphological Reconstruction for Footprint Image
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
Noisy iris segmentation with boundary regularization and reflections removal
Image and Vision Computing
User identification using user’s walking pattern over the ubiFloorII
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
A face and palmprint recognition approach based on discriminant DCT feature extraction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Entropy-based algorithms for best basis selection
IEEE Transactions on Information Theory - Part 2
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Wavelet and fuzzy neural network is the technique used in the implementation of footprint recognition system. The transformation of the footprint image is done by the wavelet to detect the edge and then according to the statistical distribution disciplinarians of different toe images the membership functions are constructed, keeping the angle and length as parameters. These obtained values are used as single judgement factor. The input to the neural network is given by computing the distance vector between the four model vectors and the comprehensive judgement vector. Template matching is based on the resultant percentage, if it is above 70 then it returns the output as matched else it returns the output as invalid or no match found. Since this wavelet-based method is based on fuzzy neural network, it reflects the different shapes of toe image subjectively and correctively, the test results show noteworthy improvements in recognition rate.