SIFT

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

矢量区域填充算法（包括汉字提取生成） 算法(Vector area filling algorithm (including the extraction of Chinese characters generated) algorithm)

bresenham画直线，WIN32，计算机图形学基础类源代码(bresenham画直线)

说明：  用于三维空间坐标系变换的7参数模型，在设计坐标系变换的各行业应用中用的最多，从数学角度来说也是最严密的转换方法。 由于结果中最多可求得七个转换参数，即三个平移参数、三个旋转参数(Ex、Ey、Ez)和一个尺度缩放因子(m)，因此，通常也被称为七参数法。 (Three-dimensional coordinate system transformation for the 7 parameter model, coordinate system transformation in the design of applications using the most, the industry, from the mathematical point of view, the conversion is the most rigorous methods. Since the results can be obtained up to seven transformation parameters, ie three translation parameters, three rotation parameters (Ex, Ey, Ez) and a zoom scale factor (m), therefore, often referred to as seven-parameter method.)

人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测人脸检测(Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection Face Detection)

该算法可以应用于计算机视觉的物体识别以及3D重构中。(The algorithm can be applied to object recognition in computer vision and 3D Reconstruction.)

YUV Quantization using VS2010

rgb to HSV，很有用，调试成功，可以应用(rgb to HSV，#include "stdafx.h" #include <iostream.h> void main(float R, float G, float B, float& H, float& S, float&V) { // r,g,b values are from 0 to 1 // h = [0,360], s = [0,1], v = [0,1] // if s == 0, then h =-1 (undefined) float min, max, delta,tmp tmp = R>G?G:R min = tmp>B?B:tmp tmp = R>G?R:G max = tmp>B?tmp:B V = max // v delta = max- min if( max != 0 ) S = delta/max // s else { // r = g = b = 0 // s = 0, v is undefined S = 0 H = 0 return } if (delta == 0){ H = 0 return } else if(R == max){ if (G >= B) H = (G- B)/delta // between yellow & magenta else H = (G- B)/delta+ 6 } else if( G == max ) H = 2+ ( B- R )/delta // between cyan & yellow else if (B == ma)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

说明：  该书介绍的用VC实现图像处理，其中包括一些图像处理知识的介绍(The book described the realization of image processing using VC, including some knowledge of image processing introduction)