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.