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A robust face identification against lighting fluctuation for lock control

机译:锁定控制照明波动的强大脸识别

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Lock-control is one of the most important security. This paper presents a face identification system for the lock-control. This system is robust for the fluctuation of the size and incline of face and lighting condition. There are two main processes in the face identification: 1) extraction of a face from input image and normalization of the size and incline of the face image, 2) matching of facial features (eye, nose and mouth) which is robust for lighting fluctuation. In order to achieve high reliability, the normalization process searches inner corners of eyes and then applies affine transformation to the face image according to the positions of the detected inner corners. The matching is performed on facial features by new template matching which uses 'sectionally adaptive correlation' for robustness against lighting fluctuation. Thresholds of the matching are determined by statistical estimation. When the system identifies a registered person, if unlocks the door. We have implemented this system and tarried out same experiments. The results show good feasibility of the lock control system and its robustness against lighting fluctuation.
机译:锁控制是最重要的安全性之一。本文介绍了锁控制的脸部识别系统。该系统对于面部和照明条件的尺寸和倾斜度的波动是稳健的。面部识别中有两个主要过程:1)从输入图像提取面部的面部和面部图像的尺寸和倾斜度,2)面部特征(眼睛,鼻子和嘴)匹配,这对于照明波动是鲁棒的。为了实现高可靠性,归一化过程搜索眼睛的内角,然后根据检测到的内角的位置将仿射变换应用于面部图像。通过新的模板匹配对面部特征进行匹配,这对照明波动的鲁棒性使用“截面自适应相关”。匹配的阈值由统计估计确定。当系统识别注册人时,如果解锁门。我们已经实施了该系统并达到了相同的实验。结果表明,锁控制系统的良好可行性及其防止照明波动的鲁棒性。

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