Abstract
Fingerprint plays a fundamental role in community security and criminal investigation, such as forensic investigation, law enforcement, customs access and public security organs. This can also help to provide a more enjoyable and secure life to people. Various machine learning and neural network approaches have been proposed for fingerprint acquisition, detection, classification, and analysis. In this survey, we present an up-to-date literature evaluation of fingerprint classification algorithms and fingerprint application in the area of criminal investigation. Firstly, we discuss the characteristics of fingerprint and the application in criminal investigation. In addition, we analyze and compare machine learning algorithms of fingerprint in terms of classification, matching, feature extraction, fingerprint and finger-vein recognition, and spoof detection. Finally, we highlight the challenges in the fingerprint analysis and discuss the future directions.
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