NDLI: Latent fingerprint matching

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Latent fingerprint matching

Content Provider	Indraprastha Institute of Information Technology, Delhi
Author	Sankaran, Anush Vatsa, Mayank Singh, Richa
Abstract	Latent fingerprint comparison evidences are used in the court of law for more than 100 years. Manual matching of latent fingerprints is challenged by subjectivity and inconsistency in terms of results and is not scalable for large scale applications. Automating the process of latent fingerprint matching will practically equip forensic examiners in criminal investigation. However, a “lights-out” automated latent fingerprint matching system is still nascent from being used in a real time environment. Several research challenges in the development of an automated matching system are identified as: (1) lack of public latent fingerprint databases available for research, (2) low information content and partial fingerprint availability in latent fingerprints, (3) presence of background noise and non-linear ridge distortion in latent fingerprints, and (4) need of an established scientific procedure for matching latent fingerprints. A comprehensive survey in the growth of latent fingerprint matching, from a computational and algorithms perspective, is provided in this report. The whole process of automated latent fingerprint matching is divided into five definite stages and the research gaps in each of the stages are individually analyzed. Also, the limitations in manual matching of latent fingerprints are studied to gain insights as well as to set a baseline for an automated system. The major discussions in this survey include: (1) encourage researchers to create and establish results in public latent fingerprint databases, (2) to focus on the individual stages of a latent fingerprint matching system and approach them independently, and (3) explore the scope for using some non-standard fingerprint features, when minutiae extraction becomes challenging.
File Format	PDF
Language	English
Access Restriction	Open
Subject Keyword	Automated latent fingerprint matching ACE-V methodology Survey IAFIS
Content Type	Text
Resource Type	Technical Report
Subject	Data processing & computer science

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