IMPLEMENTATION OF AN IDENTIFICATION SYSTEM WITH FACIAL IMAGE PROCESSING (EIGENFACE) USING MATLAB APPLICATION

Nur Dua Fathansyah Atan, Reni Rahmadewi, Damar Adzani Susanto, Wisnu Kuncoro Jati
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Abstract

Facial recognition has emerged as a prominent personal identification system, especially in the industrial sector where traditional attendance card machines have been prevalent. However, manual systems pose several drawbacks, including susceptibility to fraud, lack of flexibility, and resource wastage in card production. To address these issues, this research proposes a shift from card-based attendance systems to a facial recognition-based system using MATLAB application. The study aims to design an identification system based on the eigenface method to process facial images. It begins with a thorough literature review to gather relevant references. Subsequently, a specialized MATLAB application was developed for face identification, and its accuracy was tested. The research utilizes trained data consisting of 45 photos and tested data consisting of 15 photos to evaluate the system's accuracy. The test results reveal a 100% accuracy rate in system identification. Notably, the accuracy varies when identifying faces with different background images, indicating the robustness of the MATLAB application. Overall, the findings suggest that MATLAB can effectively implement an image processing attendance system using the eigenface method.
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利用 Matlab 应用程序实施面部图像处理(eigenface)识别系统
面部识别已成为一种重要的个人身份识别系统,尤其是在传统考勤卡机盛行的工业领域。然而,人工系统存在一些弊端,包括易受欺诈、缺乏灵活性以及制卡过程中的资源浪费。为了解决这些问题,本研究利用 MATLAB 应用程序提出了从基于卡片的考勤系统到基于面部识别系统的转变。本研究旨在设计一种基于特征脸方法处理面部图像的识别系统。研究首先对文献进行了全面回顾,以收集相关参考资料。随后,开发了一个专门用于人脸识别的 MATLAB 应用程序,并对其准确性进行了测试。研究利用由 45 张照片组成的训练数据和由 15 张照片组成的测试数据来评估系统的准确性。测试结果显示,系统识别的准确率为 100%。值得注意的是,在识别具有不同背景图片的人脸时,准确率也有所不同,这表明 MATLAB 应用程序具有鲁棒性。总之,研究结果表明,MATLAB 可以使用特征脸方法有效地实现图像处理考勤系统。
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