Video-based evidence analysis and extraction in digital forensic investigation

Xiao, Jianyu; Li, Shancang; Xu, Qingliang

Abstract

As a result of the popularity of smart mobile devices and the low cost of surveillance systems, visual data are increasingly being used in digital forensic investigation. Digital videos have been widely used as key evidence sources in evidence identification, analysis, presentation, and report. The main goal of this paper is to develop advanced forensic video analysis techniques to assist the forensic investigation. We first propose a forensic video analysis framework that employs an efficient video/image enhancing algorithm for the low quality of footage analysis. An adaptive video enhancement algorithm based on contrast limited adaptive histogram equalization (CLAHE) is introduced to improve the closed-circuit television (CCTV) footage quality for the use of digital forensic investigation. To assist the video-based forensic analysis, a deep-learning-based object detection and tracking algorithm are proposed that can detect and identify potential suspects and tools from footages.

Citation

Xiao, J., Li, S., & Xu, Q. (2019). Video-based evidence analysis and extraction in digital forensic investigation. IEEE Access, 7, 55432-55442. https://doi.org/10.1109/ACCESS.2019.2913648

• Journal Article Type: Article
• Acceptance Date: Apr 16, 2019
• Online Publication Date: Apr 26, 2019
• Publication Date: May 7, 2019
• Deposit Date: Nov 6, 2019
• Publicly Available Date: Nov 7, 2019
• Journal: IEEE Access
• Electronic ISSN: 2169-3536
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Pages: 55432-55442
• DOI: https://doi.org/10.1109/ACCESS.2019.2913648
• Keywords: General Engineering; General Materials Science; General Computer Science
• Public URL: https://uwe-repository.worktribe.com/output/3733121