Design of Smartdoor for Live Face Detection Based on Image Processing Using Physiological Motion Detection

2022 2nd International Seminar on Machine Learning, Optimization, and Data Science (ISMODE) Pub Date : 2022-12-22 DOI:10.1109/ISMODE56940.2022.10180411

Rizky Naufal Perdana, Budhi Irawan, C. Setianingsih, Dian Rezky Wulandari, Ivan Satrio Pamungkas, Fajri Nurfauzan, Adinda Ophelia Putri Sakinah, Muhammad Raihan Ramadhan

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Abstract

In the current era, technology is developing very rapidly, especially in the field of image processing, technological developments can help and facilitate human work. The purpose of image processing is to learn how to process images to detect objects. This project has the aim of implementing real face detection based on image processing in the smart door design. The physiological motion detection system can recognize the difference between real faces and photo imitations based on facial reflexes in the eyes and mouth. The methods used for face detection are Histogram Oriented Gradient and Haar-Cascade, motion detection of facial reflexes using the Support Vector Machine. The result of this project concludes that the smart door system with physiological motion detection that has been designed successfully performs real face detection, the average accuracy rate is 93.5% and photo imitation faces have an average of 90.7% based on eye reflex motion detection. and mouth.

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基于生理运动检测图像处理的实时人脸检测智能门设计

在当今时代，技术发展非常迅速，尤其是在图像处理领域，技术的发展可以帮助和便利人类的工作。图像处理的目的是学习如何处理图像来检测物体。本课题的目的是在智能门设计中实现基于图像处理的真实人脸检测。生理运动检测系统可以根据眼睛和嘴巴的面部反射来识别真实人脸和照片模拟人脸的区别。用于人脸检测的方法是直方图定向梯度和haar级联，使用支持向量机进行面部反射的运动检测。本课题的研究结果表明，设计成功的具有生理运动检测的智能门系统进行了真实人脸的检测，基于眼反射运动检测的平均准确率为93.5%，模拟照片人脸的平均准确率为90.7%。和嘴。

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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2022 2nd International Seminar on Machine Learning, Optimization, and Data Science (ISMODE)

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