Fingerprint matching using graph structure based symmetric ternary pattern

Abstract

Fingerprint matching, one of the sophisticated biometric authentication techniques, is popular for its easy implementation, persistent nature of the fingerprint and non-similarity nature of two fingerprints. Uniqueness of fingerprint is characterized by distinctive features present in fingerprint image. This paper presents a novel relational descriptor based fingerprint matching process using pattern matching concept called Multi-Variant Symmetric Ternary Pattern (MVSTP). Orientation and illumination invariant local descriptor MVSTP extract distinct features from fingerprint image by referring non-overlapping neighbor pixels in symmetric way with respect to source pixel positioned at the center of 5×5 pixel area. After feature extraction from query fingerprint image and stored fingerprint images in the database, features are compared to find similarity match. MVSTP aims to increase fingerprint matching accuracy in contrast with other processes by addressing challenges related to fingerprint pattern’s appearance variation with slight orientation and the variations present in image properties. The computational proficiency of the proposed fingerprint matching process is tested on FVC 2004 database and local database of fingerprint images with higher note of matching accuracy, manifesting its intensity in the process.