强劲的单应符合一套由此而匹配的图像点

根据：一种可识别破碎图形的特殊广义Hough变换方法 论文，在matlab上做的实验源码，有模版生成，广义哈夫变换代码-In accordance with: A broken identifiable graphics special generalized Hough transform methods papers, in matlab to do experiments on the source, there are template generation, generalized Hough transform code

全局Retinex彩色图像恢复,VC++实现，效果不错，还原真实色彩，与直方图均衡化比较-Global Retinex color image restoration, VC++ to achieve good results, restoring true colors, compared with the histogram equalization

matlab编写的对极几何约束算法，用来剔除角点跟踪过程中的离散点-matlab prepared for a very geometric constraint algorithm, used to remove corner to track discrete points in the process of

摄像头标定实现，基于opencv实现，需要先安装opencv-Camera calibration realize, based on the opencv realize the need to install opencv

使用OPENCV进行运动目标跟踪，在Visual C++ 2005 环境中使用新算法实现多运动目标的跟踪和检测。-this is a object motion tracking system with Visual c++ 2005 and opencv。it can process successly check and track multi-objects。

位图文件的处理说明-bitmap file processing note

针对传统方法难以可靠估计图像中纹理单一区域像素点视差的问题,将纹理分析应用于立体匹配中,提 出图像分块整体匹配的方法。首先用LBP/C纹理分析方法对图像纹理进行描述 然后进行基于区域生长的扩张检 测,得到纹理单一图像块 最后对图像块进行整体匹配,得到纹理单一区域的稠密视差图。对国际标准图像进行测试, 结果表明该算法能提高纹理单一区域稠密视差图的精度,具有实用价值 -Due to the difficulty of getting disparity of less textured pixels with traditional approach, block matching algorithm with texture analysis was put forward. First, the images were described by LBP/C texture analysis. Then the expansion detection based on region growing was performed, and the less textured blocks were acquired. Finally the dense disparitymap of less textured area was obtained through block matching. The proposed algorithm was tested with the international standard image data and comparedwith some existing algorithms. The experimental results show that the proposed algorithm can improve the accuracy of disparitywhen handling less textured areas and can be used in practic

课题用的背景差程序，可用于彩色图像处理。-topic with the background of poor procedures can be used to color image processing.

Contourtlet十分有用的介绍。供参考。-Contourtlet very useful introduction. For reference.

这是一个自编的应用边缘提取和傅立叶描述子来进行数字的表述和识别-This is a self-application of edge detection and Fourier descriptors for the number of statements and identification