Forensic Face Portrait Fabrication and Identification

Authors

  • Akshay Arebail
  • Prasad Jadhav
  • Omkar Wadkar
  • Abhijeet More

DOI:

https://doi.org/10.37591/joces.v12i1.902

Keywords:

Forensic face sketch, face sketch construction, face recognition, criminal identification, deep learning, machine locking, two step verification

Abstract

In today's world, the general crime rate is increasing by the day, and law enforcement agencies must discover ways to speed up the overall process and assist them in bringing criminals to justice. Face recognition technology, for example, might be used to identify and authenticate the perpetrator. The traditional strategy is to employ forensic sketch artists' hand-drawn face sketches to identify the offender; updating this would necessitate identifying the culprit by comparing the hand-drawn sketch to the law enforcement department's database. The traditional strategy is to employ forensic sketch artists' hand-drawn face sketches to identify the criminal; updating this would mean using computergenerated face sketches. The sketch is compared to the law enforcement department's database in order to identify the culprit. This approach would have numerous limitations with current technologies and would be time consuming due to a scarcity of forensic sketch artists in comparison to the rising crime rate.

References

Kiani Galoogahi H, Sim T, Lucey S. Correlation filters with limited boundaries. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015; 4630–4638.

Frowd CD, Hancock PJ, Carson D. EvoFIT: A holistic, evolutionary facial imaging technique for creating composites. ACM Trans Appl Percept (TAP). 2004 Jul 1; 1(1): 19–39.

Frowd C, Petkovic A, Nawaz K, Bashir Y. Automating the processes involved in facial composite production and identification. In IEEE 2009 Symposium on Bio-inspired Learning and Intelligent Systems for Security. 2009 Aug 20; 35–42.

Tang X, Wang X. Face sketch recognition. IEEE Trans Circuits Syst Video Technol. 2004 Jan 30; 14(1): 50–7.

Yuen PC, Man CH. Human face image searching system using sketches. IEEE Trans Syst Man Cybern Part A: Syst Hum. 2007 Jun 18; 37(4): 493–504.

Klare B, Jain AK. Sketch-to-photo matching: a feature-based approach. In SPIE Biometric technology for human identification VII. 2010 Apr 14; 7667: 11–20.

Han H, Klare BF, Bonnen K, Jain AK. Matching composite sketches to face photos: A component-based approach. IEEE Trans Inf Forensics Secur. 2012 Nov 21; 8(1): 191–204.

Song Y, Zhang J, He S, Bao L, Yang Q. Learning to hallucinate face images via component generation and enhancement. arXiv preprint arXiv:1708.00223. 2017 Aug 1.

Wang N, Gao X, Li J. Random sampling for fast face sketch synthesis. Pattern Recognit. 2018 Apr 1; 76: 215–27.

Huang YJ, Lin WC, Yeh IC, Lee TY. Geometric and textural blending for 3d model stylization. IEEE Trans Vis Comput Graph. 2017 Jan 25; 24(2): 1114–1126.

Lin SS, Morace CC, Lin CH, Hsu LF, Lee TY. Generation of escher arts with dual perception. IEEE Trans Vis Comput Graphs. 2017 Jan 27; 24(2): 1103–1113.

Sheng B, Li P, Gao C, Ma KL. Deep neural representation guided face sketch synthesis. IEEE Trans Vis Comput Graph. 2018 Aug 20; 25(12): 3216–3230.

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Published

2022-05-26

Issue

Vol. 12 No. 1 (2022)

Section

Articles

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