Authentication is the process of verifying one’s identity, and one of its implementation is in taking attendances in university’s lectures. Attendance taking is a very important matter to every academic institution as a way to examine students’ performance. Signature based attendance taking can be manipulated. Therefore it has problems in verifying the attendance validity. In this final project, a real time eigenface based face recognition is implemented in an application to do attendance taking. The input face image is captured using a webcam. The application itself is built in C#, utilizing EmguCV library. The application is developed using Visual Studio 2015. Face detection is done with Viola-Jones algorithm. The eigenface method is used to do facial recognition on the detected face image. In this final project, a total of 8 testings are done in different conditions. From the testings, it is found that this application can recognize face images with accuracy as high as 90% and as low as 6.67%. This solution can be used as an alternative for real-time attendance taking in an environment with 170 lux light intensity, webcam resolution of 320 x 240 pixel, and the subject standing 1 meter away while not wearing spectacles. The average recognition time is 0.18125 ms.
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机译:身份验证是验证个人身份的过程,其实现之一是参加大学的讲座。考勤对于每个学术机构来说都是非常重要的事情,是考核学生表现的一种方式。可以操纵基于签名的出勤方式。因此,在验证出勤有效性方面存在问题。在这个最终项目中,在应用程序中实现了基于实时特征脸的人脸识别以进行考勤。使用网络摄像头捕获输入的面部图像。应用程序本身是使用EmguCV库在C#中构建的。该应用程序是使用Visual Studio 2015开发的。人脸检测使用Viola-Jones算法完成。特征脸方法用于对检测到的脸部图像进行脸部识别。在这个最终项目中,总共在不同条件下进行了8个测试。从测试中发现,该应用程序可以识别高达90%到6.67%的人脸图像。该解决方案可以用作实时出勤的替代方案,该环境在光通量为170 lux,网络摄像头分辨率为320 x 240像素,受试者不戴眼镜的情况下站立1米的环境中。平均识别时间为0.18125毫秒。
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