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基于SUFT的特征提取与匹配，内涵详细的文档说明，很好的实现了特征提取与匹配，该方法较基本的SIFT有很大的提高(Extraction and matching of features based on SUFT, detailed content of the documentation, very good realization of the feature extraction and matching, SIFT the method is basic is greatly improved)

这个代码可以获取一种颜色可以生成10进制的数，和一个16进制的数(the code can get a color can generate 10 to the 229 number, and a few of the 229 16)

该程序主要实现图像的无损压缩，具体算法包括： （1）整数小波变换＋SPIHT无损压缩 其中整数小波可以采用JPEG2000提供的5－3小波，也可以采用S＋P变换，本程序均已给出。 （2）DPCM＋算术编码 DPCM采用的是JPEG中采用的方法； （3）JPEG－LS标准 JPEG－LS的无损压缩性能非常好，超过JPEG2000。(The program mainly realize lossless image compression, the specific algorithm include: (1) integer wavelet transform SPIHT Integer Wavelet lossless compression which can be used to provide the 5-3 wavelet JPEG2000, can also adopt the S P transform, the procedures are given. (2) DPCM arithmetic coding DPCM is used in JPEG methodology (3) JPEG-LS standard JPEG-LS lossless compression of very good performance, more than JPEG2000.)

bgslibrary_x86_v1.9.2,是MFC的实现文件，包含37种背景减除算法，对于做目标提取的研究非常有用。(The BGSLibrary was developed by Andrews Sobral and provides an easy-to-use C++ framework based on OpenCV to perform background subtraction (BGS) in videos. )

有关数字图像处理的一些源码，可以实现一些处理图像的功能，但要配合数字摄像机使用(Digital image processing of the number of source, you can achieve the functions of image processing, but with the use of digital cameras)

bmp文件的读取,2,8,16,24bit自适配(bmp file read,2、8、16、24bit adjust)

说明：  在VC++下基于MRF来进行的图像分割源代码(In VC++ For MRF-based image segmentation source code)

该文档描述了如何使用sketchup制作3D模型，并上传到google的3D仓库。(This document describes how to create 3D models using sketchup and uploaded to google' s 3D warehouse.)

用openCV实现，用Camshift算法实现彩色目标跟踪(openCV,color object tracking usingCamshift)

程序将界面与数据处理分开，界面采用MFC的对话框模板，对注册、训练、识别和主界面分别建立一个类，通过消息处理函数与用户进行交互，利用多线程来实时显示图像。 数据处理又分为了CFaceAlign（人脸检测+几何归一化）、CLightPrep（光照归一化）、CFaceFeature（Gabor特征提取）、CSubspace（计算Fisherface子空间）四个类，还有一个类 CFaceMngr 负责管理界面与数据之间的交流。这样的程序结构使对界面和算法彼此独立，互不影响。 每个类的具体方法请见相应头文件中的注释。(The program will interface with the data processing separate interface using MFC dialog template, registration, training, recognition and the main interface, respectively, to create a class that interacts with the user through a message handler, using multiple threads to display images in real time.   Data processing is divided into a CFaceAlign (Face Detection+ geometric normalization), CLightPrep (illumination normalization), CFaceFeature (Gabor feature extraction), CSubspace (computing Fisherface subspace) four categories, as well as a class is responsible for managing CFaceMngr interface and data exchange between. Such a program structure allows for interfaces and algorithms are independent of each other. Specific methods of each class, see the comments in the appropriate header files.)