基于Haar级联和LBP分类器的面部识别

Anirudha B Shetty, Bhoomika, Deeksha, Jeevan Rebeiro, Ramyashree
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引用次数: 45

摘要

人脸识别是一种用于人脸检测的生物识别技术。利用人脸识别技术对多媒体照片中的人脸进行验证或识别。随着社会的发展,人们对人脸识别的需求越来越大。人脸的检测和识别已经在世界范围内发展起来。它欠安全的需求,如授权,国家安全和其他重要情况。面部检测有很多算法。本文对两种用于分类的人脸识别技术Haar级联和局部二值模式进行了比较。结果表明,Haar级联的精度比局部二值模式高,但执行时间比局部二值模式长。
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Facial recognition using Haar cascade and LBP classifiers

Facial Recognition is the biometric technique used in face detection. The task for validating or recognizing a face from the multi-media photographs is done using facial recognition technique. With the evolution of advanced society the requirement for face identification has been really important. Detection and identification of faces has been grown worldwide. It owes the demand for security such as authorization, national safety and other vital circumstances. There are number of algorithms for facial detection. This paper aspires to present the comparison of two face recognition techniques Haar Cascade and Local Binary Pattern edified for the classification. As a result the accuracy of Haar Cascade is more than the Local Binary Pattern but the execution time in Haar Cascade is more than Local Binary Pattern.

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