smooth

介绍基于彩色不变理论的SIFT算法（CSIFT算法）的文章，文章是英文的(Color change based on the theory introduced SIFT algorithm (CSIFT algorithm) article, the article is in English)

pdf文件转化为图片.pdf 文件转化为图片VC代码实现。(from pdf to image)

基于SIFT+Kmeans+LDA的图片分类器的实现源码。 博文参考：http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html(The pictures classifier based on SIFT, Kmeans and LDA. Blog Reference: http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

I WANT SOURCE CODE FOR IMAGE SEGMENTATION

该函数用来实现快速离散余弦变换。该函数利用2N点的快速付立叶变换来实现离散余弦变换(This function is used to implement fast discrete cosine transform. 2N points of the function using the fast Fourier transform to achieve the discrete cosine transform)

说明：  MFC结合VTK做图像处理的程序，实现了图像的显示和缩放功能。(MFC combines VTK to do image processing procedures, to achieve an image display and the zoom feature.)

通过对二维人脸图片的特征提取进行三维人脸的重建(Through the two-dimensional face image feature extraction for three-dimensional reconstruction of human faces)

图形图像正交变换，离散余弦变换，VC++实现。(Graphic image orthogonal transform, discrete cosine transform, VC++ to achieve.)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)