搜索资源列表
MyBitmapImg
- 本程序实现位图的读写,均衡化,滤波,LBP,LTP特征提取以及基于LBP,LTP和卡方距离,最近邻分类的人脸识别,批量给图片改名等功能-The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square d
LBPandPCA
- 为有效解决局部二元模式(LBP)在人脸识别特征提取时维数过高的问题,提出了一种结合LBP特征和主成分分析(PCA)的人脸识别方法.-To effectively solve the local binary pattern (LBP) feature extraction in face recognition problem of high dimensionality, we propose a combination of LBP features and principal compon
LBP1
- 用lbp实现纹理特征提取,并分类说明: 一共有三个m文件,一个是lbp.m, 存放主要的lbp算法, 一个是getmapping,用以做算法的辅助函数, 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹,并在文件夹中添加相应的图片, 具体的图片名字见lbptest.m的代码,运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法,有256种。-With lbp achieve texture feature ext
SILTP
- 提取图像纹理描述符,针对LBP特征的不足,该代码具有尺度不变性和对噪声的鲁棒性-Image texture descr iptor extraction, the features of LBP, the code has scale invariance and robustness to noise
LBP_opencv
- 用opencv实现LBP的图像纹理特征提取,实现旋转不变性-LBP with opencv image texture feature extraction to achieve rotational invariance
LGBP-feature
- 提取Gabor特征,LBP特征,LGBP特征代码-extract Gabor feature,LBP feature and LGBP feature.
l
- lbp进行特征提取,以及lbp的旋转不变性-lbp feature extraction, as well as the rotational invariance lbp
face_lbp
- LBP纹理特征提取,主要是针对人脸表情的动态纹理特征进行分类!-LBP texture feature extraction, the main classification dynamic texture feature recognition is facial expression!
LBPTOP_VC
- 带有时间信息的LBP特征(LBPTOP)的提取及使用举例 C/C++版本-LBPTOP feature extraction (C/C++ version)
bag-of-words
- 图像特征点提取词袋模型,添加LBP特征的选择,融合两种特征进行图像的特征提取-bag of words in images
LocalBinaryPattern
- LBP算法的C++实现,对于做表情识别特征提取很有帮助-LBP algorithm C++ implementation, very helpful for face recognition feature extraction
lbp007
- 图像特征提取 cslbp和各种lbp代码-cslbp MATLAB
LBP_train_main
- LBP特征的提取以及SVM分类器的训练,提供一个框架-LBP feature extraction and SVM classifier training, to provide a framework
25292626
- 为了实现复杂环境下的人脸特征有效表达,提出一种改进的梯度方向直方图(HOG)人脸识别方法.首先以人脸图像网格作为采样窗口并在其上提取 HOG特征;然后将所有网格 HOG特征向量进行组合,实现整个人脸特 征表达;最后采用最近邻分类器进行识别.另外,比较了该方法与Gabor小波和局部二值模式(LBP)2种著名的人脸 局部特征表示方法的优劣.实验结果表明,在调优的 HOG参数下,在具有光照和时间环境等复杂变化的FERET人 脸库中,较少维数的 HOG特征比LBP特征有更好的表现,而且 HO
LBP2
- 提取lbp特征,基于opencv的。简单代码-lbp feature
LBP_PHOG
- LBP+PHOG特征提取,再利用SVM进行分类训练,需要安装libsvm,注意修改样本路径和数量。-LBP+PHOG feature extraction, re-use SVM classification training, you need to install libsvm, pay attention to modify the path and the number of samples.
vlfeat-0.9.20-bin
- 特征提取的工具包,实现各种特征,如hog,lbp,sift.-Feature extraction kit achieve a variety of features, such as hog, lbp, sift.
Image_Feature
- 图像特征提取代码,包括LBP、HOG、Haar、Zernike矩、Hu矩特征,.h文件有如何调用的说明。-LBP feature、HOG feature、Haar feature、Moment feature
LBP
- 提取图像的lbp纹理特征,然后进行向量表示- Lbp extracted texture features of the image, and then vector representation
DeepLearnToolbox_CNN_lzbV2.0
- DeepLearnToolbox_CNN_lzbV2.0 深度学习,卷积神经网络,Matlab工具箱 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusberg