A Triplet Based Approach for Indexing of Fingerprint Database for Identification

Abstract

This paper presents a model-based approach which efficiently retrieves correct hypotheses using properties of triangles formed by the triplets of minutiae as the basic representation unit. We show that the uncertainty of minutiae locations associated with feature extraction and shear does not affect the angles of a triangle arbitrarily. Geometric constraints based on characteristics of minutiae are used to eliminate erroneous correspondences. We present an analysis to characterize the discriminating power of our indexing approach. Experimental results on fingerprint images of varying quality show that our approach efficiently narrows down the number of candidate hypotheses in the presence of translation, rotation, scale, shear, occlusion and clutter.