Modified geometry of ring-wedge detector for sampling Fourier transform of fingerprints for classification using neural networks
Dinesh Ganotra, Joby Joseph, Kehar Singh · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Sampling of the Fourier transforms (FTs) of fingerprints is studied with neural networks to detect regions useful for their classification. Ring-wedge detector (RWD) is modified and simulated to sample such regions. The output of the detector is propagated through a three-layer backpropagation neural network (BPNN) for checking the classification performance. Modified detector's performance is also compared with that of RWD. It has been found that fingerprints scanned at 500 dpi resolution contain useful information for their classification in a band of width 20 pixels with inner radius approx. 60 pixels.