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Face Recognition for Attendance System Detection

机译:考勤系统检测的人脸识别

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摘要

These days, biometric authentication methods begin growing rapidly as one of promising authentication methods, besides the conventional authentication method. Almost all biometrics technologies require some actions by user, which are the user needs to place funds on the scanner to set the fingers or the hand geometry detection. The user shall stand still in a fixed position in front of the camera for iris or retina identification purpose. The face recognition method has several external advantages compared to the other biometric methods because this method can be done passively without explicit action or should be held by the user since the face image can be obtained by the camera from a certain distance. This method can be especially useful for mission and supervision. This research would develop and implement the face recognition system consists of four stage process. The four-stage process were face detection process using skin color detection and Haar Cascade algorithm, alignment process that contains face features normalization process, feature extraction process, and classification process using LBPH algorithm. Furthermore, the process would be continued to current system replacement with the system that has been built. The experimental results show that the system can recognize the faces captured automatically by the camera accurately.
机译:如今,除了传统的身份验证方法外,生物特征身份验证方法作为有希望的身份验证方法之一也开始迅速发展。几乎所有的生物识别技术都需要用户采取一些措施,即用户需要在扫描仪上投入资金以设置手指或手部的几何形状。为了虹膜或视网膜识别的目的,使用者应在相机前的固定位置静止不动。与其他生物特征识别方法相比,面部识别方法具有一些外部优势,因为该方法可以被动执行而无需明确的动作,或者应由用户握持,因为可以通过相机从一定距离获得面部图像。这种方法对于任务和监督尤其有用。本研究将开发并实现由四个阶段组成的人脸识别系统。这四个阶段包括使用肤色检测和Haar Cascade算法的面部检测过程,包含面部特征归一化过程的对齐过程,特征提取过程以及使用LBPH算法进行分类的过程。此外,该过程将继续进行,以当前的系统替换为已构建的系统。实验结果表明,该系统可以准确识别摄像机自动捕捉到的人脸。

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