A Conditional Selection of Orthogonal Legendre/Chebyshev Polynomials as a Novel Fingerprint Orientation Estimation Smoothing Method

Abstract

In this paper, a new approach to fingerprint ridge orientation estimation smoothing by a conditional selection of orthogonal polynomials is proposed. This method can smooth the low coherence and consistency areas of fingerprint OF. Also, it is able to estimate the Orientation Field (OF) for fingerprint areas of no ridge information This method does not need any basis information of Singular Points (SPs). The algorithm uses a consecutive application of filtering-based and model-based orientation smoothing methods. A Gaussian filter has been employed for the former. The latter conditionally employs one of the orthogonal polynomials such as Legendre and Chebyshev type I or II, based on the results of the filtering based stage. The experiments have been conducted on the fingerprint images of FVC2000 DB2_A, FVC2004 DB3_A and DB4_A. The results show coarse ridge orientation estimation improvement even in very poor quality images where the orientation information cannot be clearly extracted.