密集点匹配opencv程序

1、/由于cvut版本进行了更新，致使该工程不能在最新cvut版本下编译，请使用工程包含的cvut库进行编译#include "cv.h"#include "highgui.h"#include "cvut/cvut.h"#include <iostream>#include <fstream>#include <string>#include <vector>using namespace std;using namespace cvut;#pragma comment(lib,"

2、;cxcore")#pragma comment(lib,"cv")#pragma comment(lib,"highgui")/#define REAL_TIME_MATCHING_SHOWint main(int argc,char* argv)Image<uchar> temp("image/Luxor02StereoSm2.jpg");Image<uchar> left(temp.size().width/2,temp.size().height,8,3);Image<uchar>

3、 right(temp.size().width/2,temp.size().height,8,3);/分割图像int i,j,t,k;for (i=0;i<temp.height;+i) j=0;for (;j<temp.width/2;j+) for (t=0;t<temp.channels;+t) left(i,j,t) = temp(i,j,t);j+;for (k=j+1,j=0;k<temp.width;+k,+j) for (t=0;t<temp.channels;+t) right(i,j,t) = temp(i,k,t); left.show(&

4、quot;left"); right.show("right",400,0); cvWaitKey(); left.close(); right.close();/*特征匹配*/cout<<"特征匹配"int depth_count = 0;vector<vector<int> > depth(left.width*left.height,vector<int>(3);vector<int> depth_buf(3);/匹配窗口大小/int win_size = 9;Matrix<

5、;double> left_wins(left.width-win_size/2-win_size/2,win_size*win_size*3,1);Matrix<double> right_wins(left.width-win_size/2-win_size/2,win_size*win_size*3,1);/设定最大可能视差/int depth_max = 10;int depth_min = left.height;bool is_match = false;int l,m,n;for (i=win_size/2;i<left.height-win_size/2

6、;i+) cout<<i<<" "/* 建立第i行所有的源向量和目的向量 */for (int k=win_size/2;k<left.width-win_size/2;k+) int p=0,q=0;for (l=i-win_size/2;l<=i+win_size/2;l+) for (m=k-win_size/2;m<=k+win_size/2;m+) for (n=0;n<3;n+) left_wins(k-win_size/2,p+,0) = left(l,m,n);for (m=k-win_size/2;m<

7、=k+win_size/2;m+) for (n=0;n<3;n+) right_wins(k-win_size/2,q+,0) = right(l,m,n);/遍历极线进行匹配for (j=win_size/2;j<left.width-win_size/2;j+) depth_buf0 = i;depth_buf1 = j;/* 初始最大误差 */double cos_val = 0.9;int index=0;is_match = false;for (int k=j;k<min(left.width-win_size/2,j+depth_max);k+) /* 计算向

8、量误差 */double cos_temp = 0,val1 = 0,val2 = 0,val3 = 0;for (int u=0;u<left_wins.cols;+u) val1 += left_wins(j-win_size/2,u,0)*right_wins(k-win_size/2,u,0);val2 +=left_wins(j-win_size/2,u,0)*left_wins(k-win_size/2,u,0);val3 +=right_wins(k-win_size/2,u,0)*right_wins(k-win_size/2,u,0);cos_temp = val1/s

9、qrt(val2)/sqrt(val3);/* 判断是否匹配 */if (cos_temp > cos_val)depth_buf2 = k-depth_buf1;cos_val = cos_temp;index = k;is_match = true;if (is_match) depth_min = depth_buf2<depth_min?depth_buf2:depth_min;depthdepth_count = depth_buf;depth_count+;is_match = false;/* 实时匹配显示 */#ifdef REAL_TIME_MATCHING_SH

10、OWcvCircle(left.cvimage,cvPoint(j,i),1,CV_RGB(255,255,255);cvCircle(right.cvimage,cvPoint(index,i),1,CV_RGB(255,255,255); left.show("left",0,0);right.show("right",400,0);cvWaitKey();left.close();right.close();#endifcout<<"完成"<<endl;/*显示深度图像*/cout<<"最小视差："<<depth_min<<endl<<"最大视差："<<depth_max<<endl;Image<uchar> depth_image(left.size(),8,1);for (i=0;i<depth.size();i+) depth_image