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自己关于TVL1方法的改进 用来去除人脸上面的光照得到人脸的纹理图像，对于光照下人脸识别有相当大的作用。也可以用来定位,Their own methods to improve on TVL1 people face to face to remove the light to be Face of texture images, for face recognition under illumination a significant role. Can also be used to pos
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基于形态学商图像的光照归一化算法.复杂光照条件下的人脸／P,~J1是一个困难但需迫切解决的问题，为此提出了一种有效的光照归一化算法．
该方法根据面部光照特点，基于数学形态学和商图像技术对各种光照条件下的人脸图像进行归一化处理，并且将它
发展到动态地估计光照强度，进一步增强消除光照和保留特征的效果．与传统的技术相比，该方法无须训练数据集以
及假定光源位置，并且每人只需一幅注册图像，在耶鲁人脸图像库B上的测试表明，该算法以较小的计算代价取得了
优良的识别性能．-Face recogn
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这个c#编写的程序，用来对人脸图像进行预处理，从而提升人脸识别算法的性能。这里提出了3种用于人脸识别的图像预处理的光照归一化算法，即：Multiscale retinex和anisotropic 和isotropic平滑方法。-The c# Preparation procedures used for face image preprocessing, so as to enhance the performance of face recognition algorithms. Here p
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source code for light normalisation presented by Ralph Gross in this paper
@inproceedings{RGross_AVBPA_2003,
author = "Ralph Gross and Vladimir Brajovic",
title = "An Image Preprocessing Algorithm for Illumination Invariant Face Recognition",
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this document shows how to normalize illumination and reducing the negative effects of illumination on face recognition.
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This code is the implementation of Mahalnobis SOM algorithm published in this article.
Face recognition under varying illumination using Mahalanobis self-organizing map
S Aly, N Tsuruta, RI Taniguchi - Artificial Life and Robotics, 2008 - Springe
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基于LPP的人脸识别模块，运用matlab7.0编写，识别率达到70 以上，能够很好的识别不同姿势，光照，表情的变化-LPP-based face recognition module, using matlab7.0 writing, over 70 recognition rate can be a very good identification of the different positions, illumination, expression changes in
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INface toolbox for illumination invariant face recognition
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基于光照不变量的人脸识别-Face Recognition,Based on Illumination Invariant
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采用光照归一化算法，可以用于人脸识别的预处理。-Illumination normalization algorithm for face recognition.
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此文的目的有三个：第一，当地连续均值量化变换特征是提出照明和传感器敏感操作在目标识别上。其次，注册稀疏Winnows网络分割，提出了加快原分类。最后，特点和分类相结合对于正面人脸检测任务。检测结果列
为MIT + CMU系统和BioID数据库。关于这人脸检测器，接收器操作特征曲线BioID数据库产生最好的结果公布。对于结果麻省理工学院的中央结算系统+数据库相当于国家的最先进的脸探测器。一个人脸检测算法的MATLAB版本可以从http://www.mathworks.com/matlabce
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The INFace (Illumination Normalization techniques for robust Face recognition) toolbox v2.0 is a collection of Matlab functions and scr ipts intended to help researchers working in the field of face recognition.
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光照不变的人脸识别问题是目前比较关注的一个大问题，本文章为你提供了一种新方法-a good paper for illumination face recognition method
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illumination-robust face recognition via sparse representation
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face recognition in various illumination
using utp mathod. used in PCA algorithm
select image whivh you want to recognize and it will give you 3 result. as per the selection of image
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解决人脸识别系统中，人脸图像的尺寸归一化、位置校准、光照补偿、直方图均衡化、特征提取的工作-Solve the face recognition system, the size of the face image normalization, position calibration, illumination compensation, histogram equalization, feature extraction work
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2014年人脸识别的最新研究进展，包含了表情识别、光照变化等等各种人脸识别问题的研究-2014 Face of the latest research progress, including the study of face recognition, face recognition illumination change and so on various issues
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Face recognition has been one of the most interesting and important research fields in the past two decades. The reasons come the need of automatic recognitions and surveillance systems, the interest in human visual system on face recognition, and th
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非匀速运动模糊光照和姿态人脸识别，英文文献-Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose
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In this paper,we address the effect of illumination on the face detection and the face recognition problem by introducing a novel illumination invariant method, called OptiFuzz. It is an optimized fuzzy-based illumination invariant method to solve th
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