Face recognition for remote database backup system

• Main Authors: Mohamed Din, Aniza, Ahmad, Faudziah, Mohamad Mohsin, Mohamad Farhan, Ku-Mahamud, Ku Ruhana, Theab, Mustafa Muwafak
• Format: Conference or Workshop Item
• Language: English
• Published: 2011
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/9499/1/063.pdf; http://repo.uum.edu.my/9499/; http://ieeexplore.ieee.org.eserv.uum.edu.my/xpl/articleDetails.jsp?tp=&arnumber=6316622&queryText%3Dfaudziah+ahmad

Face recognition is one of the most interesting applications in the image processing field.To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features.In this research a face recognition model is developed.The dataset used is of different face images. Neural Networks technique, specifically Multilayer Perceptron (MLP) model with Back-Propagation learning algorithm and Template Matching approach are implemented in model developed.The face recognition model developed is then applied on a remote database backup system.Template matching approach is found to give a higher percentage of matching accuracy and a faster result can be obtained compared to MLP as no learning process is required