CCTV quality assessment for forensics facial recognition analysis

Mohamad Firham Efendy Md Senan, Siti Norul Huda Sheikh Abdullah, Wafa Mohd Kharudin, Nur Afifah Mohd Saupi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Closed-circuit television (CCTV) is used to perform surveillance recordings, and it is one of the most common digital devices that provide digital evidence for the purpose of forensic analysis. In video forensic analysis, the footage with the target subject or object is extracted out from the CCTV recordings for further analysis. However, the quality of these recordings are often poor due to several factors, such as the type of the camera, the configuration, and also the position of the camera. The results of forensic face recognition depend highly on the quality of the CCTV recordings. Poor quality of CCTV recordings would reduce the confidence level of the face recognition result, thus would not make a strong evidence to be presented in a court of law. The objective of this research is to conceptualise a framework for quality assessment in CCTV evidence to be used in forensic face recognition analysis. The method of this research was divided into two phases. Initial phase covered CCTV evidence testing phase where the experiment was done based on different types of CCTV camera with different resolutions, and distances between the subject and the camera. In the second phase, the face of the subjects were compared to the face taken during the enrolment phase. The score obtained from the forensic face recognition system would be based on the camera resolutions, types of camera, distances, and also the changes of ranking score after applying the enhancement process such as Bicubic to the facial images. The results were analyzed for quality assessment towards these parameters. In general, the evaluation of scoring and ranking decreased as the distance increased. The face also could not be detected by the system when they were taken more than 5 meters distance from the camera. The highest score of 5.95 was obtained by using resolution 1280 × 720 at distance of 3 meters taken by camera model ACTI E62. The Bicubic enhancement method improved the scoring and ranking especially with the camera model that have low resolution modes.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages649-655
Number of pages7
ISBN (Electronic)9781509035182
DOIs
Publication statusPublished - 7 Jun 2017
Event7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017 - Noida, Uttar Pradesh, India
Duration: 12 Jan 201713 Jan 2017

Other

Other7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017
CountryIndia
CityNoida, Uttar Pradesh
Period12/1/1713/1/17

Fingerprint

Television
Cameras
Networks (circuits)
Face recognition
Video recording
Digital devices
Quality assessment
Video cameras
Testing
Ranking

Keywords

  • Bicubic Enhancement Method
  • CCTV
  • Facial Recognition
  • Quality Assessment
  • Video Forensics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

Cite this

Senan, M. F. E. M., Sheikh Abdullah, S. N. H., Kharudin, W. M., & Saupi, N. A. M. (2017). CCTV quality assessment for forensics facial recognition analysis. In Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering (pp. 649-655). [7943232] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONFLUENCE.2017.7943232

CCTV quality assessment for forensics facial recognition analysis. / Senan, Mohamad Firham Efendy Md; Sheikh Abdullah, Siti Norul Huda; Kharudin, Wafa Mohd; Saupi, Nur Afifah Mohd.

Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc., 2017. p. 649-655 7943232.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Senan, MFEM, Sheikh Abdullah, SNH, Kharudin, WM & Saupi, NAM 2017, CCTV quality assessment for forensics facial recognition analysis. in Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering., 7943232, Institute of Electrical and Electronics Engineers Inc., pp. 649-655, 7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017, Noida, Uttar Pradesh, India, 12/1/17. https://doi.org/10.1109/CONFLUENCE.2017.7943232
Senan MFEM, Sheikh Abdullah SNH, Kharudin WM, Saupi NAM. CCTV quality assessment for forensics facial recognition analysis. In Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc. 2017. p. 649-655. 7943232 https://doi.org/10.1109/CONFLUENCE.2017.7943232
Senan, Mohamad Firham Efendy Md ; Sheikh Abdullah, Siti Norul Huda ; Kharudin, Wafa Mohd ; Saupi, Nur Afifah Mohd. / CCTV quality assessment for forensics facial recognition analysis. Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 649-655
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