—基于机器学习的人脸识别算法的设计与实现

第 1 页基于机器学习的人脸识别算法的设计与实现承诺人签名： 日期： 年 月 日基于机器学习的人脸识别算法的设计与实现摘 要人脸识别技术是一种新型的生物特征认证技术。人脸识别技术也是一个非常活跃的研究领域，涵盖了许多领域，例如数字图像处理。随着人们对应用程序需求的增长，面部识别技术趋向于大量使用，使用微芯片和标准化。人脸检测是快速准确识别人脸的先决条件。其目的是检测图像背景下的人脸，并将其与数据中的人脸进行比较，以实现人脸识别。第 2 页本文以 python 为开发技术，前端实时检测摄像头人脸，人脸识别主要是使用 mtcnn 做人脸提取，使用 facenet 做人脸特征提取，通过余弦相似度分类进行人脸识别。系统界面简洁、识别迅速、使用方便。 本文首先介绍了人脸识别系统的现状及其发展背景，然后讨论了系统设计目标，系统要求和总体设计计划，并详细讨论了人脸识别系统的详细设计和实现。 系统最后进行面部识别 并对系统进行特定的测试。 关键词：人脸识别；python；机器学习第 3 页Design and implementation of face recognition algorithm based on machine learningABSTRACTFace recognition technology is a new type of biometric authentication technology. Face recognition technology is also a very active research area, covering many fields, such as digital image processing. As the demand for application programs grows, facial recognition technology tends to be used in large quantities, using microchips and standardization. Face detection is a prerequisite for rapid and accurate face recognition. Its purpose is to detect the face in the background of the image and compare it with the face in the data to achieve face recognition.This article uses python as the development technology. The front end detects the camera's face in real time. Face recognition mainly uses mtcnn for face extraction, and facenet for face feature extraction, and uses cosine similarity classification for face recognition. The system interface is simple, quick to identify, and easy to use.T...