Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/8075
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dc.contributor.authorArunalatha, J.S.
dc.contributor.authorTejaswi, V.
dc.contributor.authorShaila, K.
dc.contributor.authorAnvekar, D.
dc.contributor.authorVenugopal, K.R.
dc.contributor.authorIyengar, S.S.
dc.contributor.authorPatnaik, L.M.
dc.date.accessioned2020-03-30T10:18:03Z-
dc.date.available2020-03-30T10:18:03Z-
dc.date.issued2015
dc.identifier.citationProcedia Computer Science, 2015, Vol.54, , pp.482-490en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8075-
dc.description.abstractFingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. � 2015 The Authors.en_US
dc.titleFIVDL: Fingerprint Image Verification using Dictionary Learningen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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