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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38434
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Traditional forensic methods, like hand-drawn sketches, often fall short in quickly identifying suspects, making the process both slow and resource-intensive. This paper introduces an innovative application designed to streamline this task. Through a simple drag-and-drop interface, users can upload sketches and match them with entries in police databases, significantly boosting the speed and accuracy of suspect recognition. By integrating deep learning and cloud technology, this tool builds on existing algorithms to deliver higher precision and ease of use. Earlier methods have had trouble aligning sketches with photographs, especially when orientations differ. Our application overcomes these issues, merging the art of sketching with modern technology to enhance forensic work. Testing reveals promising accuracy, though ongoing improvements are needed to fully meet the demands of law enforcement. This research aims to offer a real-world solution, tackling past limitations and making suspect identification faster and more efficient for investigators.
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Publication Date
5/10/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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