Lucas_Kanade

粘连字符切分，带测试图片，效果不错 (Adhesion character segmentation, with test images, good results)

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 extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

一个自适应的滤波处理的方法，可以对图像有很好的处理效果。(An adaptive filtering method of treatment can have a good image the effect of treatment.)

亚像素方面的相关源码!!!相信对你的学习会有帮助!(Related to source sub-pixel area!!! That would be helpful to your learning!)

1、去条带噪声（通道均衡）程序 2、去冲击噪声程序 3、KSVD程序 均为matlab源代码(1 to band noise (channel equalization) program 2, to the impact of noise program 3, KSVD program Matlab source code are)

小波包去噪C + +源代码，包括信号小波包分解，，最优树的选择，并重建一个,可以直接使用。 (Wavelet packet denoising C++ source code, including the signal wavelet packet decomposition, the optimal choice of the tree, and rebuild a can be used directly.)

说明：  Ostu分割方法实现 根据原理编写Ostu程序，对cameraman灰度图片进行分割；并对获得的前景与背景，分别再进行一次分割；(Implementation of Ostu segmentation method According to the principle, the Ostu program is compiled to segment the gray image of cameraman, and the foreground and background are segmented again;)

数字水印参考代码，分别用checksum，lsb，patchwork等方式嵌入水印，并且附带计算信噪比和消除水印的代码(Digital watermark reference code checksum lsb in patchwork way embedded watermark and accompanying calculated signal-to-noise ratio and eliminate the watermark code)

这是我的一骗小课程报告，内容主要是有关矢量数据压缩方法的简介，以及自己的一些见解。(VECTOR IMAGE DETECT)

说明：  此源码可对图像进行Ncut分割，并且集成了特征提取和SVM分类的功能。(This source can be Ncut image segmentation, and integrates the feature extraction and SVM classification function.)