High-performance Face Detection Using Mct and Adaboost Algorithm: Simulation Of Face Detection

The proposed system is a novel hardware architecture of face-detection engine for mobile applications. Here MCT(Modified Census Transform) and Adaboost learning technique as basic algorithms of face-detection engine. It is designed, implemented and verified the hardware architecture of face-detection engine for high-performance face detection and real- time processing. The face-detection chip is developed by verifying and implementing through FPGA and ASIC. The developed ASIC chip has advantage in real-time processing, low power consumption, high performance and low cost. So this chip can be easily used in mobile. Face detection performance is known to be highly influenced by variations in illumination. Especially in mobile environment, the illumination condition is dependent on the surroundings (indoor and outdoor), time, and light reflection, etc. The proposed face- detection method is designed to detect in the variable illumination conditions through the MCT techniques, which can reduce the effects of illumination by extracting the structural information of objects.