Abstract

Accurate and efficient identification have become a vital requirement for forensic application due to diversities of criminal activities. A recent advancement in biometric technologywhich is equipped with computational intelligence techniques is replacing manual identification approaches in forensic science. Biometrics is a fundamental verification mechanism that identifies individuals on the basis of their physiological and behavioral features. These biometric expansions are easily observable in different forensic identification areas, e.g. face, fingerprint, iris, voice, handwriting, etc. The effectiveness of biometricssystem lies in different recognition processes which include feature extraction, feature robustness and feature matching. The emergence of forensic biometrics covers a wide range of applications for physical and cybercrime detection. Forensic Biometrics also overcomes the loopholes of traditional identification system that were based on personal probabilities. It is considered as a fundamental shift in the way criminals are detected. The present study describes the contribution and limitations of biometric science in the field of forensic identification.

Highlights

  • Accurate and efficient identification have become a vital requirement for forensic application due to diversities of criminal activities

  • A recent advancement in biometric technology which is equipped with computational intelligence techniques is replacing manual identification approaches in forensic science

  • The present study describes the contribution and limitations of biometric science in the field of forensic identification

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Summary

Introduction

Accurate and efficient identification have become a vital requirement for forensic application due to diversities of criminal activities. These biometric expansions are observable in different forensic identification areas, e.g. face, fingerprint, iris, voice, handwriting, etc. A biometric system is a pattern recognition device that acquires physical or behavioral data from an individual, extracts a salient feature set from the data, compares this feature set against the features set stored in the database and provides the result of the comparison.

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Conclusion

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