The implementation of eigenface algorithm for face recognition in attendance system

Vincentius Kurniawan, Arya Wicaksana, Maria Irmina Prasetiyowati
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引用次数: 6

Abstract

Technology advancement has brought in mobility and flexibility into the workplaces in contrast to the old days. Workers are demanded to perform their job at places other than their office. The well-known long-established attendance systems that are widely used in workplaces are heavily depending on technologies such as the Radio Frequency Identification (RFID) and fingerprint. Both technologies have limitation especially when it comes to flexibility and mobility. Thus, this research proposes an attendance system that addresses the mentioned condition. The attendance system is built using Android and web technologies with geolocation extraction feature and biometric technology: the face recognition. The Eigenface algorithm is chosen for face recognition process in the system. In addition to that, Euclidean distance is used for calculate the distance between input image and the training image. There are variables in this research that may disturb the recognition process: lighting, distance between the face and the camera, and hardware specifications, which are not taken into consideration. Based on the implementation and testing process, the overall accuracy of the system is 86.67%.
特征脸算法在考勤系统中人脸识别的实现
与过去相比,技术进步给工作场所带来了流动性和灵活性。工人们被要求在办公室以外的地方工作。众所周知,在工作场所广泛使用的考勤系统在很大程度上依赖于无线射频识别(RFID)和指纹等技术。这两种技术都有局限性,尤其是在灵活性和移动性方面。因此,本研究提出了一个解决上述情况的考勤系统。考勤系统采用Android和web技术构建,具有地理位置提取功能和生物识别技术:人脸识别。人脸识别过程采用特征脸算法。此外,还使用欧几里德距离来计算输入图像与训练图像之间的距离。本研究中有一些变量可能会干扰识别过程:光照、人脸与相机之间的距离以及硬件规格,这些都没有被考虑在内。根据系统的实现和测试过程,系统的总体准确率为86.67%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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