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similaritymeasure
- 在对图像进行识别和分类过程中，相似性测量可以作为一种判别策略，目的是刻画图像之间的本质特性。-In the image recognition and classification process, the similarity measure can be used as a discriminating strategy aimed portray the essential characteristics of images.
SPM_SC
- This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper Linear Spatial Pyramid Matching using Sparse Coding for Image Classification .基于空间金字塔匹配的稀疏编码，用于图像检索，识别与分类-This package contains the Matlab codes im
aotutexingdetuojiyingwenzifushibie
- 提出了一种基于整体（凹凸）特性的脱机大写体英文字母识别方法。首先计算字母图像的赋值背景，再从中提取凹凸特性，然后根据凹凸特性构建分类表进行分类识别。-This paper presents an off-line capitalization method based on the whole (concavity) feature. First, calculate the background of the letter image, and then extract the convex
hog_svm
- 这文件夹包含了，hog特征提取，多类SVM分类器，数据库，图像识别(This folder contains the hog feature extraction, multi class SVM classifier, database, image recognition)
Character_Recognition
- 本程序主要参照论文，《基于OpenCV的脱机手写字符识别技术》实现了，对于手写阿拉伯数字的识别工作。识别工作分为三大步骤：预处理，特征提取，分类识别。预处理过程主要找到图像的ROI部分子图像并进行大小的归一化处理，特征提取将图像转化为特征向量，分类识别采用k-近邻分类方法进行分类处理，最后根据分类结果完成识别工作。 程序采用Microsoft Visual Studio 2010与OpenCV2.4.4在Windows 7-64位旗舰版系统下开发完成。并在Windows xp-32位系统下测试
svm_images
- 识别图像，利用HOG特征，svm分类方法，区别率较高(Recognition of images, the use of HOG features, SVM classification method, the distinction rate is higher)
40746336sift-mlab
- 检测并提取图像的SIFT特征，用于图像识别和分类(Identify and extract the SIFT feature points in the image for image recognition and classification)
ViolaJones_version0b_bin
- 用adaboost对人脸检测，利用haar特征对积分图像进行训练，得到强弱分类器(Face detection is done by AdaBoost, and integral image is trained by Haar feature, and the strong and weak classifier is obtained.)
Data
- 人脸识别图像集，用于人脸识别与分类，40类别，每类别5张，分训练和测试样本。(Face recognition image set is used for face recognition and classification. 40 categories, 5 for each category, are divided into training and testing samples.)
car
- 车辆图像集，彩色，用于车辆识别与分类，也可用于车牌号识别。(Vehicle image set, color, for vehicle recognition and classification, and also for license plate recognition.)
s1
- 识别给出图像与图像库中的图像进行比对识别分类(The recognition and classification of the image and the image in the image library are identified.)
2DPCA
- 基于ORL人脸库的2DPCA图像识别与人脸重建代码，采用最近邻域进行分类(2DPCA image recognition and face reconstruction code based on ORL face ,using the nearest neighbor classification.)
基于PCA的人脸识别
- 使用PCA算法对人脸图像进行处理，使用adaboost算法训练分类器，对训练集中的20个人每人五张照片进行训练，对测试集中的同样多的照片进行识别，可以得到很高的识别率