AUTOMATED FINGERPRINT IDENTIFICATION SYSTEM: A CRITICAL REVIEW OF TECHNOLOGY, ACCURACY, AND FORENSIC APPLICATIONS

Abstract

Background: Fingerprint identification is a dependable and widely used tool in forensic science because friction ridge patterns are unique and permanent. Traditional manual fingerprint inspection is time-consuming and requires significant human effort, particularly when comparing fingerprints across large criminal databases. The Automated Fingerprint Identification System (AFIS) has greatly enhanced forensic identification by allowing for the automated storage, processing, and comparison of fingerprints.

Objective:
The purpose of this review is to objectively investigate the Automated Fingerprint Identification System (AFIS)'s creation and operational principles, as well as to assess its forensic applications, benefits, limitations, and emerging technological breakthroughs in fingerprint identification.

Methods:
This review draws on previously published research articles, review papers, and forensic science studies about fingerprint identification and AFIS technology. Relevant literature was gathered from scholarly databases and peer-reviewed journals to evaluate the technological processes and forensic applications of automated fingerprint recognition systems.

Results:
According to the studied research, AFIS considerably enhances the speed, accuracy, and efficiency of fingerprint identification. It allows for the quick comparison of latent fingerprints to massive digital databases, which aids law enforcement in suspect identification, forensic intelligence, and cold-case investigations. Poor-quality fingerprints, expensive implementation costs, and the necessity for expert verification can all have an impact on system performance.

Conclusion:
AFIS has become an indispensable instrument in modern forensic investigations. Ongoing improvements in artificial intelligence, machine learning, and advanced imaging technologies are projected to increase the accuracy, reliability, and efficiency of automated fingerprint identification systems in future forensic applications.