Faculty Member Publish Research on Human Face Recognition Using PCA

Dr. Iyad Ibrahim Abbas and Assistant Lecturer Mohammed Ihsan Safi, faculty members from the Department of Electrical Engineering, presented their research at the Fifth International Conference on Current Research in Computer Science and Information Technology, held at the University of Human Development in Sulaymaniyah. Their paper, titled “Calculating the Distinction Rate of Human Faces Using Different Classification Theories Based on Principal Component Analysis (PCA)”, focuses on designing a system for recognizing human faces by aggregating images of a single person’s face to enhance the PCA algorithm.

The research utilized the ORL face database for training and testing the model, employing three recognition methods: Euclidean Distance, Squared Euclidean Distance, and Manhattan Distance. Results showed a 100% recognition rate for Squared Euclidean Distance, 98% for Euclidean Distance, and 95% for Manhattan Distance.