Ridges of Evidence: Emerging Technologies in Fingerprint Science and Automated Identification
Keywords:
Fingerprint Science, Automated Fingerprint Identification System (AFIS), Latent Fingerprint Detection, Artificial Intelligence, Biometric IdentificationAbstract
Fingerprint science is one of the most scientifically sound and dependable methods to identify human beings in forensic investigations. This review covers the biological basis of fingerprint science and traditional ridge classification, as well as advanced automated fingerprint identification systems and AI-powered technologies. It covers developments in the science of detecting, visualizing, collecting and reading latent prints, as well as Automated Fingerprint Identification Systems (AFIS), including the use of explainable artificial intelligence (XAI) and novel computational tools to enhance recognition accuracy and efficiency. The review also tackles issues related to poor quality fingerprints, algorithmic bias and interoperability of databases among fingerprints, as well as the law related to automated fingerprint evidence in India. In summary, the use of sophisticated imaging techniques, biometric matching, and intelligent computational tools has revolutionized fingerprint analysis, making it a quicker, more objective, and almost foolproof aspect of modern forensics.
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