A major approach for fingerprint recognition today is to extract minutiae from fingerprint images and to perform fingerprint matching based on the number of corresponding minutiae pairings. One of the most difficult problems in fingerprint recognition has been that the recognition performance is significantly influenced by fingertip surface condition, which may vary depending on environmental or personal causes.
Addressing this problem, this paper presents a fingerprint recognition algorithm using phase-based image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of fingerprint images makes possible to achieve highly robust fingerprint recognition for low-quality fingerprints. Experimental evaluation using a set of fingerprint images captured from fingertips with difficult conditions (e.g., dry fingertips, rough fingertips, allergic-skin fingertips) demonstrates an efficient recognition performance of the proposed algorithm compared with a typical minutiae-based algorithm.
Biometric authentication has been receiving extensive attention over the past decade with increasing demands in automated personal identification. Biometrics is to identify individuals using physiological or behavioral characteristics, such as fingerprint, face, iris, retina, palm-print, etc. Among all the biometric techniques, fingerprint recognition is the most popular method and is successfully used in many applications.
Typical fingerprint recognition methods employ feature-based image matching, where minutiae (i.e., ridge ending and ridge bifurcation) are extracted from the registered fingerprint image and the input fingerprint image, and the number of corresponding minutiae pairings between the two images is used to recognize a valid fingerprint image. The feature-based matching provides an effective way of identification for majority of people.
However, it has been known that there are a number of people whose fingerprints could not be identified by the featurebased methods due to special skin conditions, where feature points are hard to be extracted by image processing. The ratio of people who have such difficult fingerprints varies depending on race, sex, age, job groupings, etc., but it is said that one to five percentage of total population may fall into this category.
Addressing this problem, this paper proposes an efficient fingerprint recognition algorithm using phase-based image matching — an image matching technique using the phase components in 2D Discrete Fourier Transforms (DFTs) of given images. The technique has been successfully applied to highaccuracy image registration tasks for computer vision applications, where estimation of sub-pixel image translation is a major concern. In this paper, we demonstrate that this technique is highly effective also for fingerprint matching. The use of Fourier phase information of fingerprint images makes possible highly reliable fingerprint matching for low-quality fingerprints whose minutiae are difficult to be extracted.