Paper Details

ABSTRACT

Digital images are subject to a wide variety of distortions during processing, compression, storage and reproduction any of which may result in a degradation of visual quality. Many practical and commercial systems use digital image compression when it is required to transmit or store the image over network bandwidth limited resources.JPEG 2000 compression is the most popular image compression standard because it provides higher compression ratio but did not reconstruct edges of an image perfectly. 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, andWSQ), especially at high compression ratios. The experiments also illustrate that the proposed algorithm is robust to extract minutiae.