Design of a Neural Networks Classifier for Face Detection

Face detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation allows real-time processing, but has higher cost and time to-market. The objective of this work was to implement a classifier based on neural networks MLP (Multi-layer Perception) for face detection. The MLP was used to classify face and non-face patterns. The system described using C language on a P4 (2.4 Ghz) to extract weight values. Then a Hardware implementation achieved using VHDL based Methodology. We targeted Xilinx FPGA as the implementation support.