Status: published
In forensic science, composite sketches are a critical tool for identifying suspects based on eyewitness testimony. However, the traditional process relies on trained forensic artists and is slow, subjective, and produces an analog image that cannot be easily matched against digital police databases. GenFace is a Java-based desktop application that solves this problem by providing a complete, end-to-end solution. The system features a user-friendly JavaFX interface that allows users, even without artistic skill, to build a composite sketch using a drag-and-drop library of facial features. The core innovation lies in its integration with cloud-based artificial intelligence. Upon completion, the sketch is sent to an AI backend powered by AWS Rekognition, which compares it against a secure database of reference mugshots. The system returns the most likely matches with a similarity score, providing law enforcement with immediate, actionable intelligence. By bridging the gap between sketch creation and digital recognition, GenFace aims to significantly reduce investigation time and improve the accuracy of suspect identification.
Keywords: Forensic Science, Composite Sketch, Face Recognition, JavaFX, AWS Rekognition, Deep Learning, Heterogeneous Face Recognition, E-Governance.