Name
Abstract | ||
|---|---|---|
Facial recognition has played an essential role in digital forensics due to the widespread use of digital technology such as CCTV, mobile phones, and digital cameras. Therefore, the growing volume of multimedia files (photos and videos), in particular, are a valuable source of evidence and the ability to identify culprits’ is invaluable. Despite significant efforts that have been given to this area, facial recognition suffers from several drawbacks in achieving recognition. These reasons are caused by photos conditions issues such as bad illumination, facial orientation, facial expression, photo quality, accessories (e.g., hat, glasses), and aging. The Facial-Forensic Analysis Tool (F-FAT) provides a technique that aids the forensic investigation in terms of the automatic facial recognition. It is a holistic system that is developed to collect, exam, and analyse multimedia evidence (photos and videos) using a multi-algorithmic fusion approach to overcome the weaknesses in individual algorithms and achieve a better accuracy for identification. The proposed approach also helps to reduce the cognitive load placed upon the investigator by providing a variety of forensic analyses such as, geo-location, facial modification, and social networks, to enable quicker answers to queries. This tool has also been designed based upon a case management concept that helps to manage the overall system, provide robust authentication, authorization and chain of custody. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.diin.2018.04.008 | Digital Investigation |
Keywords | DocType | Volume |
Digital forensic,Face recognition,Multi-algorithm,Fusion | Journal | 26 |
ISSN | Citations | PageRank |
1742-2876 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiba Al-kawaz | 1 | 0 | 0.34 |
| Nathan L. Clarke | 2 | 421 | 41.93 |
| Steven M. Furnell | 3 | 1002 | 104.31 |
| Fudong Li | 4 | 69 | 13.10 |