Flawless Fingerprint Matching Approach based on SVM Classifier

Abstract

Elastic distortion of fingerprints is such of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watchlist and deduplication applications. In a well-known application, malicious users make out purposely distort their fingerprints to evade identification. In this paper, we proposed latter algorithms to regard and rectify skin distortion based on a single fingerprint image. Distortion detection is viewed as a two-class classification problem, for which the registered ridge orientation map and period map of a fingerprint are used as the feature vector and a SVM classifier is used to perform the classification task. Distortion rectification is viewed as a regression problem, to what place the input is a improper fingerprint and the product is the distortion field. To resolve this problem, a database of distinct distorted reference fingerprints and corresponding distortion fields is built in the offline stage, and earlier in the online turn, the nearest neighbor of the input fingerprint is found in the recommendation database and the corresponding distortion work is used to resolve the input fingerprint into a balanced one.

Authors and Affiliations

K. Amulya, V. Priyanka, Ch. Sudheer Kumar

Keywords

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  • EP ID EP23908
  • DOI http://doi.org/10.22214/ijraset.2017.4202
  • Views 279
  • Downloads 10

How To Cite

K. Amulya, V. Priyanka, Ch. Sudheer Kumar (2017). Flawless Fingerprint Matching Approach based on SVM Classifier. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(4), -. https://europub.co.uk/articles/-A-23908