Automatically choosing appropriately sized structuring elements to eliminate useless components in fingerprint image

Abstract

Fingerprints are useful for biometric purposes because of their well known properties of distinctiveness and persistence over time. However, owing to skin condition or incorrect finger pressure, some fingerprint images contain useless components. They are often mistaken for the terminations that are an essential minutia of a fingerprint. Mathematical Morphology (MM) is one powerful tool in image processing. The performance of MM is heavily dependent on structuring elements (SEs), but finding an optimal SE is a difficult and nontrivial task. In this work, we focus on automatically choosing an appropriate SE for eliminating useless components of fingerprint images using linear time Euclidean distance transform algorithm. We exploit the property that these useless components are thinner than fingerprint ridges. So, we estimate the width of useless components and fingerprint ridges using Euclidean distance transform values, and then provide a linear time algorithm to eliminate the useless components. We have developed a novel algorithm for the binarization of fingerprint images. The information of distance transform values can be obtained directly from the binarization phase. The results show that using this method on fingerprint images with useless components is faster than existing methods and achieves better quality than earlier methods.