Latent fingerprint identification system for crime scene investigation

The traditional means of criminal investigation used in Nigeria is often unreliable and leads to innocent people's wrongful detention and a lack of justice for deserving offenders. The poor record-keeping and weaknesses in Nigeria's investigation process significantly contribute to the high levels of crime and insecurity in Nigeria. To tackle these issues, this project provides an implementation of a fingerprint identification system to improve criminal investigation in Nigeria. Three image processing algorithms and a Convolutional Neural Network classification algorithm were explored for matching performance. The Convolutional Neural Network classification model performed better than the three image processing algorithms with an accuracy of 64.44%. The final system provides a web interface with database interaction to send a fingerprint image and meta data to receive match results and potential suspect (criminal) information.
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, May 2021
forensic techniques, biometrics