Extraction algorithm of principal lines and rotation method for non-contacting fingerprint authentication

In conventional systems of fingerprint authentication for personal identification, identification rates are reduced when the surface of the fingerprint input device is soiled or damaged by contact. Moreover, 2-value information on ridges and valleys is fundamentally insufficient for evasion of impersonation (cheating). We have examined the possibility of non-contact fingerprint authentication to address these problems. Problems caused by contact can be avoided and information on the form and color of a finger can be acquired, if the input method is changed. In this study, a method for extracting the principal lines (valley lines) of a fingerprint from a color picture of a fingertip from a non-contact visual input is proposed as an approach to non-contact fingerprint authentication. In the proposed technique, first a wavelet transform is performed on the input image and the edge component equivalent to the valley line is separated from the signal by which zone division was carried out. Then, binarization and thinning are performed on the edge component. This processing is performed on the Y and Z components of an XYZ table color system, and valley lines are extracted complexly. A non-contact input method offers the further advantage of being able to perform acquisition of finger form. Although rotation processing of a fingerprint image is very complicated in the conventional systems, effective use of form information makes the processing simple in the proposed technique. The central line of a finger is computed using form information, and the axis of rotation is set as the tip of the finger. Accurate rotation is possible if rotation processing is performed by an affine transform so that the central line may be made perpendicular.