| Summary: | 碩士 === 國立臺灣大學 === 資訊工程學研究所 === 92 === The automatic person authentication becomes more and more important as technology advances. How to build a safe and convenient identity recognition system is a hot research topic in academia and business. In this thesis, we introduce a face recognition system which is suitable under varying light conditions. The main framework can be divided into two parts: the lighting process, the intruder detection. Face recognition based on computer vision suffers from three problems: variations due to changes in pose, viewpoint, and illumination. In the practical face recognition system, we can control the viewpoint, and force the user pose manually. But it is not easy to control the lighting condition as the pose and the viewpoint. In the intruder detection, it is less discusses how to detect the intruders in face recognition, but it is essential to a complete face recognition system.
In the lighting process part, we use the quotient image algorithm to obtain the illumination part of the people. We use multi-class classifier to predict the result of the new people, and in consider of the intruder we use one-class classifier to detect intruder. Then we can obtain the confident values of the multi-class classifier and one-class classifier by training data. , and we use this two confident values to find the best match (i.e. We can combine the two confident values by the different weighting). Therefore we design a problem which is to find the weighting combination to be a classification problem. We can use this combination to enhance the robustness of our system.
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