Master’s Thesis at the University of Basrah Explores Fingerprint Liveness Detection
A master’s thesis at the College of Computer Science and Information Technology, University of Basrah, examined fingerprint liveness detection using a deep learning framework.
The thesis, presented by master’s student Aya Abdul Kareem Hameed, aimed to propose a lightweight deep learning network based on the ResNet architecture to distinguish between real and fake fingerprints. This approach offers strong generalization capabilities while reducing computational complexity, enabling higher accuracy compared to current methods in detecting spoof fingerprints.
The study highlighted the network’s ability to prevent unauthorized access, thereby enhancing overall system security. Its lightweight design also makes it suitable for real-world applications, such as mobile devices or embedded systems with limited resources.
Department of Media and Governmental Communication
