登录
首页 » matlab » LBP

LBP

于 2013-08-05 发布 文件大小:16359KB
0 180
下载积分: 1 下载次数: 151

代码说明:

  LBP(局部二值模式)特征提取,用于人脸识别,(LBP feature extraction for face recognition. . .)

文件列表:

LBP
...\extract.asv,2408,2013-08-03
...\extract.m,2435,2013-08-03
...\getLBPFea.m,2303,2013-08-03
...\IsUniform.m,416,2013-06-03
...\jingdu.asv,171,2013-08-03
...\jingdu.m,172,2013-08-03
...\kfun_rbf.m,194,2013-08-03
...\makeLBPMap.m,697,2013-08-03
...\MatLBPMap.mat,290,2013-08-03
...\multiSVMClassify.m,1330,2008-08-05
...\multiSVMTrain.m,1767,2013-08-03
...\recognition.asv,2153,2013-08-03
...\recognition.m,1983,2013-08-03
...\使用说明.txt,42,2013-08-03
...\测试样本
...\........\m-001-14.pgm,19815,2007-02-23
...\........\m-001-15.pgm,19815,2007-02-23
...\........\m-001-16.pgm,19815,2007-02-23
...\........\m-001-17.pgm,19815,2007-02-23
...\........\m-001-18.pgm,19815,2007-02-23
...\........\m-001-19.pgm,19815,2007-02-23
...\........\m-001-20.pgm,19815,2007-02-23
...\........\m-001-21.pgm,19815,2007-02-23
...\........\m-001-22.pgm,19815,2007-02-23
...\........\m-001-23.pgm,19815,2007-02-23
...\........\m-001-24.pgm,19815,2007-02-23
...\........\m-001-25.pgm,19815,2007-02-23
...\........\m-001-26.pgm,19815,2007-02-23
...\........\m-002-14.pgm,19815,2007-02-23
...\........\m-002-15.pgm,19815,2007-02-23
...\........\m-002-16.pgm,19815,2007-02-23
...\........\m-002-17.pgm,19815,2007-02-23
...\........\m-002-18.pgm,19815,2007-02-23
...\........\m-002-19.pgm,19815,2007-02-23
...\........\m-002-20.pgm,19815,2007-02-23
...\........\m-002-21.pgm,19815,2007-02-23
...\........\m-002-22.pgm,19815,2007-02-23
...\........\m-002-23.pgm,19815,2007-02-23
...\........\m-002-24.pgm,19815,2007-02-23
...\........\m-002-25.pgm,19815,2007-02-23
...\........\m-002-26.pgm,19815,2007-02-23
...\........\m-003-14.pgm,19815,2007-02-23
...\........\m-003-15.pgm,19815,2007-02-23
...\........\m-003-16.pgm,19815,2007-02-23
...\........\m-003-17.pgm,19815,2007-02-23
...\........\m-003-18.pgm,19815,2007-02-23
...\........\m-003-19.pgm,19815,2007-02-23
...\........\m-003-20.pgm,19815,2007-02-23
...\........\m-003-21.pgm,19815,2007-02-23
...\........\m-003-22.pgm,19815,2007-02-23
...\........\m-003-23.pgm,19815,2007-02-23
...\........\m-003-24.pgm,19815,2007-02-23
...\........\m-003-25.pgm,19815,2007-02-23
...\........\m-003-26.pgm,19815,2007-02-23
...\........\m-004-14.pgm,19815,2007-02-23
...\........\m-004-15.pgm,19815,2007-02-23
...\........\m-004-16.pgm,19815,2007-02-23
...\........\m-004-17.pgm,19815,2007-02-23
...\........\m-004-18.pgm,19815,2007-02-23
...\........\m-004-19.pgm,19815,2007-02-23
...\........\m-004-20.pgm,19815,2007-02-23
...\........\m-004-21.pgm,19815,2007-02-23
...\........\m-004-22.pgm,19815,2007-02-23
...\........\m-004-23.pgm,19815,2007-02-23
...\........\m-004-24.pgm,19815,2007-02-23
...\........\m-004-25.pgm,19815,2007-02-23
...\........\m-004-26.pgm,19815,2007-02-23
...\........\m-005-14.pgm,19815,2007-02-23
...\........\m-005-15.pgm,19815,2007-02-23
...\........\m-005-16.pgm,19815,2007-02-23
...\........\m-005-17.pgm,19815,2007-02-23
...\........\m-005-18.pgm,19815,2007-02-23
...\........\m-005-19.pgm,19815,2007-02-23
...\........\m-005-20.pgm,19815,2007-02-23
...\........\m-005-21.pgm,19815,2007-02-23
...\........\m-005-22.pgm,19815,2007-02-23
...\........\m-005-23.pgm,19815,2007-02-23
...\........\m-005-24.pgm,19815,2007-02-23
...\........\m-005-25.pgm,19815,2007-02-23
...\........\m-005-26.pgm,19815,2007-02-23
...\........\m-006-14.pgm,19815,2007-02-23
...\........\m-006-15.pgm,19815,2007-02-23
...\........\m-006-16.pgm,19815,2007-02-23
...\........\m-006-17.pgm,19815,2007-02-23
...\........\m-006-18.pgm,19815,2007-02-23
...\........\m-006-19.pgm,19815,2007-02-23
...\........\m-006-20.pgm,19815,2007-02-23
...\........\m-006-21.pgm,19815,2007-02-23
...\........\m-006-22.pgm,19815,2007-02-23
...\........\m-006-23.pgm,19815,2007-02-23
...\........\m-006-24.pgm,19815,2007-02-23
...\........\m-006-25.pgm,19815,2007-02-23
...\........\m-006-26.pgm,19815,2007-02-23
...\........\m-007-14.pgm,19815,2007-02-23
...\........\m-007-15.pgm,19815,2007-02-23
...\........\m-007-16.pgm,19815,2007-02-23
...\........\m-007-17.pgm,19815,2007-02-23
...\........\m-007-18.pgm,19815,2007-02-23
...\........\m-007-19.pgm,19815,2007-02-23

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • srad
    srad斑点去噪各向异性扩散滤波器,代码很短,本身该方法就含有不少的偏微分方程,看懂需要仔细研究。(srad, speckle denoising anisotropic diffusion filter)
    2014-02-08 18:03:45下载
    积分:1
  • similarityext
    基于遥感光学图像的宽网道路检索,能够快速的实现半自动道路提取,给出种子点对输入方向进行快速检索(Optical remote sensing images based on a wide network of roads retrieval, the realization of fast semi-automatic road extraction, given the input direction of the seed point for rapid retrieval)
    2009-01-20 19:32:04下载
    积分:1
  • qicheshiyan
    这是一个去背景并且进行阈值分割的程序,阈值的选择采用迭代法(This is the background to a threshold value and segmentation procedures, the threshold value of the options using the iterative method)
    2007-04-26 21:06:30下载
    积分:1
  • BP
    说明:  BP神经网络做曲线拟合,BP网络应用于曲线二次拟合(BP neural network to do curve fitting, BP network used in curve fitting quadratic)
    2008-05-26 18:33:15下载
    积分:1
  • 结构光照明荧光显微镜数据稳定性检测程序 SIMcheck-dev
    结构光照明荧光显微镜数据稳定性检测程序,非常强大(Structured light illumination fluorescence microscopy data stability testing procedures, very strong)
    2015-07-07 20:07:36下载
    积分:1
  • b-splines
    说明:  基于b样条的弹性图像配准程序 matlab实现(B-spline-based elastic image registration procedures for the realization of matlab)
    2009-08-12 16:15:26下载
    积分:1
  • IHS_fusion
    ihs融合方法,比较好用,测试通过,大家可以试试~(ihs fusion methods, better quality, tested, we can try ~)
    2010-06-22 22:24:57下载
    积分:1
  • CFAR
    利用CFAR检测SAR图像中的高亮度目标。(Detect targets with high backscattering intensities by CFAR algorithm)
    2020-12-07 18:39:21下载
    积分:1
  • NonnegJune2009
    说明:  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复,本程序实现了泊松噪声下的图像恢复,泊松噪声为信号依赖噪声,能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)
    2020-11-05 19:19:50下载
    积分:1
  • threhold-dealt
    关于阈值处理的一部分参考文献,对于图像的二值化等很有帮助,是经过精心选择的参考文件。(References on the part of the processing threshold for image binarization helpful, is carefully selected reference files.)
    2014-08-25 12:03:43下载
    积分:1
  • 696518资源总数
  • 105877会员总数
  • 14今日下载