Forensic Face Sketch

Forensic Face Sketch is a forensic sketch construction and recognition system designed to help investigators create composite suspect sketches and compare them against stored records.

The project combines a JavaFX desktop application with image storage and face recognition workflows using AWS services.

Why This Project Exists

In many investigations, eyewitnesses describe a suspect verbally while investigators or forensic artists manually construct a face sketch. That process can be slow, inconsistent, and difficult to search against existing records.

This project explores a software-assisted workflow where facial components can be assembled into a composite sketch and compared against stored image records using cloud-based recognition.

Key Features

• Composite face sketch construction using selectable facial components
• Criminal record storage and retrieval workflow
• AWS S3 integration for image storage
• AWS Rekognition-based face comparison
• Admin and investigator-style user flows
• Project report and screenshots included for reference

Tech Stack

• Java
• JavaFX
• AWS S3
• AWS Rekognition
• Database-backed record storage
• NetBeans

Repository Contents

• FinalCode.zip - legacy source code archive
• Project Report.pdf - academic project report
• Project Screenshots/ - screenshots from the application
• sketch elements/ - facial component assets used by the sketch construction workflow

System Workflow

1. User creates a composite face sketch from available facial components.
2. The application stores the sketch and related record metadata.
3. Image data is uploaded to AWS S3.
4. AWS Rekognition compares the sketch against available records.
5. Possible matches are returned for review.

Current Status

This is an older academic and research project. The core idea, screenshots, report, and implementation history are preserved, but the project would need modernization before production use.

Future Improvements

• Move legacy source code out of compressed archives
• Replace manual IDE setup with a cleaner build system
• Remove hardcoded local paths and credentials
• Add safer authentication and email configuration
• Add automated tests
• Add Docker-based local setup
• Build a modern web interface