Latent fingerprint identification system for crime scene investigation
Date
2021-05
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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.
Description
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
item.page.type
Capstone project
item.page.format
Keywords
forensic techniques, biometrics