Latent Fingerprint Identification Based on Minutiae Features

Abstract

The word biometrics originates from two Greek terms, bio means life, and metric newlinemeans to be measured. Biometrics offers a way of identifying individuals using DNA, iris, newlinefingerprints, facial features, and gait characteristics. These distinctive molecular, physical, newlineand behavioral characteristics have provided enormous research opportunities to develop newlinebiometric identification systems in recent years. Several biometric recognition systems are newlineusing face, iris, fingerprint, palm print, voice, and signature worldwide. Among all the newlinebiometric traits, fingerprints are the most popularly used biometrics because of their newlineproperties, such as ease of acquisition, uniqueness, and persistence over time. While the newlineadvancement of fingerprint recognition over several decades has led to low-cost solutions, newlinemature sensors, and advanced algorithms, the precise identification of latent fingerprints in newlinecriminal applications remains an open challenge. Latent fingerprint identification involves newlinethe retrieval of an appropriate number of fingerprints from a criminal database. Current newlineend-to-end automated latent fingerprint matching systems have not achieved significant newlinematch accuracy and speed.