Latent Fingerprint Matching Using Grey Level Co-Occurrence Matrix
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 5
Abstract
Abstract: Recognizing defendant based on impressions of fingers from crime scenes is important to law enforcement agencies. Latents are partial fingerprints with small area, contain nonlinear distortion,and are usually dirty and less distinct. Due to some of these characteristics, they have a seriously smaller number of minutiae points and thus it can be distinctly difficult to automatically match latents to plain or rolled fingerprints that are stored in law enforcement databases. The goal is to develop a latent matching algorithm that uses only minutiae information. The proposed algorithm uses a robust alignment algorithm (descriptor-based Hough transform) to align fingerprints and measures similarity between fingerprints by considering both minutiae and orientation field information.Since the proposed algorithm depend only on manually marked minutiae, it can be easily used in the law enforcement application.We can added an texture feature to improve the matching performances by using a method called gray-level co-occurrence matrix.The texture features are contrast,correlation,energy and homogeneity.The proposed approach consists of following three modules: (i) align two sets of minutiae by using a descriptor-based Hough Transform; (ii) establish the correspondences between minutiae; and (iii) compute a similarity score.
Authors and Affiliations
Riya Jose, , Abdul Ali
Keywords
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