Sensors, Vol. 23, Pages 7548: Digital Forensic Analysis of Vehicular Video Sensors: Dashcams as a Case

Sensors, Vol. 23, Pages 7548: Digital Forensic Analysis of Vehicular Video Sensors: Dashcams as a Case Sensors doi: 10.3390/s23177548 Authors: Yousef-Awwad Daraghmi Ibrahim Shawahna Dashcams are considered video sensors, and the number of dashcams installed in vehicles is increasing. Native dashcam video players can be used to view evidence during investigations, but these players are not accepted in court and cannot be used to extract metadata. Digital forensic tools, such as FTK, Autopsy and Encase, are specifically designed for functions and scripts and do not perform well in extracting metadata. Therefore, this paper proposes a dashcam forensics framework for extracting evidential text including time, date, speed, GPS coordinates and speed units using accurate optical character recognition methods. The framework also transcribes evidential speech related to lane departure and collision warning for enabling automatic analysis. The proposed framework associates the spatial and temporal evidential data with a map, enabling investigators to review the evidence along the vehicle’s trip. The framework was evaluated using real-life videos, and different optical character recognition (OCR) methods and speech-to-text conversion methods were tested. This paper identifies that Tesseract is the most accurate OCR method that can be used to extract text from dashcam videos. Also, the Google speech-to-text API is the most accurate, while Mozilla’s D...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research