Adaptive fingerprint enhancement by combination of quality factor and quantitative filters

Abstract

Fingerprint enhancement is a crucial step in automatic fingerprint recognition system, undiscriminating repeated filtering easily lead to false structure in low-quality regions of a fingerprint image. This paper presents a new adaptive enhancement algorithm that can automatically adjust the parameters of filters and the time of filtering according to the quality factors in different regions. In order to improve filtering efficiency, a template bank of 4-dimenstion scaleable array is also designed to quantize the filter and forms the basis of a new fused filter. Experimental results in eight low-quality images from FVC2004 data sets show that the proposed algorithm is higher 23.7% in Good Index (GI), and saves 54.06% time consumptions than traditional Gabor-based methods. Since the eight images are extremely bad, a little improvement is very meaningful. © Springer-Verlag Berlin Heidelberg 2005.