IDENTIFEYE: Sketch-Based Facial Analysis in Forensics

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. Keywords: Forensic identification, Suspect sketching, Deep learning, Recognition software, Law enforcement tools, Cloud technology.