This paper presents an algorithm for fingerprint matching using the Phase-Only Correlation (POC) function. One of the most difficult problems in human identification by fingerprints has been that the matching performance is significantly influenced by fingertip surface condition, which may vary depending on environmental or personal causes. This paper proposes a new fingerprint matching algorithm using phase spectra of fingerprint images. The proposed algorithm is highly robust against fingerprint image degradation due to inadequate fingertip conditions. A set of experiments is carried out using fingerprint images captured by a pressure sensitive fingerprint sensor. The proposed algorithm exhibits efficient identification performance even for difficult fingerprint images that could not be identified by the conventional matching algorithms.

This paper presents a high-accuracy image registration technique using a Phase-Only Correlation (POC) function. Conventional techniques of phase-based image registration employ heuristic methods in estimating the location of the correlation peak, which corresponds to image displacement. This paper proposes a technique to improve registration performance by fitting the closed-form analytical model of the correlation peak to actual two-dimensional numerical data. This method can also be extended to a spectrum weighting POC technique, where we modify cross-phase spectrum with some weighting functions to enhance registration accuracy. The proposed method makes possible to estimate image displacements with 1/100-pixel accuracy.