Real Time Face Recognition System

Zusatztext

Face recognition has received substantial attention from public around the world. The interest from the general public is mostly due to the recent events of terror around the world, which has increased the demand for useful security systems. In this project, Principle Component Analysis (PCA) act as efficient method to develop face recognition system. Images captured from real-time video had been analyzed by compared an input image with the database and report the image if similar. Different appearances by each person which is normal face, using spectacles, wearing cap and wearing mask was tested to determine the performance of the system. Twenty (20) persons were involved as experimental case studies to validate the efficiency of the developed system. Experimental results show 100% recognition for normal face and using spectacles, 95% of wearing cap and 45% of wearing mask.

Autorenportrait

Asrani Lit is a Research Scientist at Department of Electrical and Electronic in UNIMAS. Muhammad Shaah Fihee Misman is a Bachelor in Electronic Engineering (Computer) from Universiti Malaysia Sarawak (UNIMAS). Fariza Mahyan is a Research Scientist at Polytechnic of Kuching.

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