Fingerprint Compression Based on Sparse Representation

Fingerprint Compression Based on Sparse Representation

A new fingerprint compression algorithm based on sparse representation is introduced. Obtaining an overcomplete dictionary from a set of fingerprint patches allows us to represent them as a sparse linear combination of dictionary atoms. In the algorithm, we first construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l0-minimization and then quantize and encode the representation. In this paper, we consider the effect of various factors on compression results. Three groups of fingerprint images are tested. The experiments demonstrate that our algorithm is efficient compared with several competing compression techniques (JPEG, JPEG 2000, and WSQ), especially at high compression ratios. The experiments also illustrate that the proposed algorithm is robust to extract minutiae.

2 Thoughts to “Fingerprint Compression Based on Sparse Representation”

  1. Mahesh

    Good evening sir,
    I am Mahesh pursuing B.tech final year in warangal, telangana.
    I am doing project on “Fingerprint compression based on sparse representation” which is IEEE 2014 paper as a part of final year and need to be implemented in MATLAB.
    So i need code with explanation for my project.
    Please inform me the cost & timings to meet your office so that we will plan accordingly.

    Thanking you sir.
    Please reply to my mail as soon as possible.

  2. ajay patil

    Good evening sir,
    I am ajay patil pursuing B.tech final year in MGM nanded.
    I am doing project on “Fingerprint compression based on sparse representation” which is IEEE 2014 paper as a part of final year and need to be implemented in MATLAB.So i need code with explanation for my project.
    Thanking you sir.
    Please reply to my mail as soon as possible.

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