Design of a neural networks classifier for face detection

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Abstract

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 is to implement a classifier based on neural networks MLP (Multi-layer Perceptron) for face detection. The MLP is used to classify face and non-face patterns. The systm is described using C language on a P4 (2.4 Ghz) to extract weight values. Then a Hardware implementation is achieved using VHDL based Methodology. We target Xilinx FPGA as the implementation support. COPYRIGHT © ENFORMATIKA.

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Smach, F., Atri, M., Mitéran, J., & Abid, M. (2005). Design of a neural networks classifier for face detection. In Proceedings - WEC’05: 3rd World Enformatika Conference (Vol. 5, pp. 274–277). https://doi.org/10.3844/jcssp.2006.257.260

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