Fingerprint Compression Based On Online Dictionary Learning and Orthogonal Matching Pursuit

Abstract

A new fingerprint compression technique based on the concept of sparse representation is introduced. Given a set of fingerprint patches, an over complete dictionary is constructed and the patches are represented as a sparse linear combination of dictionary atoms. The methods prior to this used K-SVD algorithm for constructing dictionary and MP (Matching Pursuit) algorithm to solve the l0 minimization problem. The common step in all of the algorithms is that a dictionary is first constructed for predefined fingerprint image patches and for a new given fingerprint image its patches are represented according to the dictionary by computing l0 minimization. The next step is to quantize and encode the representation. This technique uses an method called ODL (Online Dictionary Learning) for dictionary construction and OMP (Orthogonal Matching Pursuit) algorithm to solve the l0 minimization problem. The results of this method are provided in this paper and compared with the results of batch and stochastic gradient method to determine the efficient compression method.

Authors and Affiliations

Dinesh. E, Ramyasridevi. R, Revathi. K, Selvam. V, Vicithra. S

Keywords

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  • EP ID EP19594
  • DOI -
  • Views 275
  • Downloads 3

How To Cite

Dinesh. E, Ramyasridevi. R, Revathi. K, Selvam. V, Vicithra. S (2015). Fingerprint Compression Based On Online Dictionary Learning and Orthogonal Matching Pursuit. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(2), -. https://europub.co.uk/articles/-A-19594