人脸识别中各种方法和颜色模型的综述

Prabhjot Singh, M. Kaur, Jaspreet Singh
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引用次数: 1

摘要

人脸传递着与人的表达状态相关的极端信息。作为人脸识别的生物识别的子类别被认为是几个应用领域的主要挑战,这些应用主要用于识别和验证目的,例如执法,银行系统的高安全性,安全系统的认证,特别是用于识别和验证人脸与其他人脸的人。在本文的综述中,主要包括三个阶段:(i)人脸表征(ii)特征提取(iii)检测与识别。人脸图像,提取其独特特征。将分类过程中的人脸图像与来自大型人脸数据集的图像进行比较。人脸识别是实时应用中最可靠和最重要的安全保障案例。本文首先对人脸识别技术进行了概述,并对其功能进行了描述。因此,它定义了目前使用的人脸识别方法,并添加了它们的优缺点。海量的人脸识别方法,加入LBP、LDA、PCA和EIGEN人脸进行识别。针对不同的面部表情情况和图像的光照情况,本文提出的一些方法也提高了人脸识别的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Review of Various Methods and Color Models in Face Recogntion
The human being face is passing on extreme information related to the person expressing state. The sub category of biometrics as face recognition is considered as a major challenge in the area of several applications significantly for the identification and verification purposes such as for law enforcement, high security in banking systems, authentication for security system and particularly for the identification and verification of the person faces with other faces. In this review paper, mainly consists of three phases: (i) Face representation (ii) Extract the features and (iii) detection and recognition. The facial images, extract the unique features. Classification process compared with the images face images from the large facial datasets. Facial recognition is a real-time application such as a reliable and most important case for security. In this review paper, first, define an overview of facial recognition and describe the functionality. Consequently, it defines face recognition methods which are currently used to add their merits and demerits. The huge number of facial recognition methods, adding LBP, LDA, PCA and EIGEN faces for recognition. The various facial expression situation and illumination of images some methods specified here also enhances the effectiveness of facial recognition.
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