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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1372

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dc.contributor.authorGanotra, Dinesh-
dc.contributor.authorJoseph, Joby-
dc.contributor.authorSingh, Kehar-
dc.identifier.citationOptics and Lasers in Engineering, 42(2), 167-177en
dc.description.abstractSampling of the Fourier transforms 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 feedforward-backpropagation neural network 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 and cropped to a size of 200×200 contain useful information for their classification in a band of width 20 pixels with inner radius approx. 60 pixels.en
dc.format.extent432494 bytes-
dc.subjectRing-wedge detectoren
dc.subjectNeural networksen
dc.titleModified geometry of ring-wedge detector for sampling Fourier transform of fingerprints for classification using neural networksen
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