OpenCV中OpenMP的使用

#include "stdafx.h"

#include "cv.h" 
#include "highgui.h" 
#include <stdio.h> 
#include <stdlib.h> 
#include <omp.h>

#pragma comment(lib,"opencv_core2410d.lib")              
#pragma comment(lib,"opencv_highgui2410d.lib")              
#pragma comment(lib,"opencv_imgproc2410d.lib")    

 

void EdgeOpenMP(IplImage *src,IplImage *dst,int thresh) 
{ 
    int height    = src->height; 
    int width     = src->width; 
    int step      = src->widthStep; 
    uchar *data1      = (uchar *)src->imageData; 
    uchar *data2      = (uchar *)dst->imageData;

    int i=step; 
    #pragma omp parallel for 
    for(i=step+1;i<height*width;i++){ 
         if(abs(data1[i]-data1[i-1])>thresh || abs(data1[i]-data1[i-step])>thresh) 
            data2[i]=255;/* 对于单通道，前后两帧差分大于门限 
            或者对于多通道前后两帧的一个指标差分大于门限，则视为边缘*/ 
         else 
            data2[i]=0; 
    } 
}

void Edge(IplImage *src,IplImage *dst,int thresh) 
{ 
    int height    = src->height; 
    int width     = src->width; 
    int step      = src->widthStep; 
    uchar *data1      = (uchar *)src->imageData; 
    uchar *data2      = (uchar *)dst->imageData;

   int i=step; 
    for(i=step+1;i<height*width;i++){ 
         if(abs(data1[i]-data1[i-1])>thresh || abs(data1[i]-data1[i-step])>thresh) 
            data2[i]=255; 
         else 
            data2[i]=0; 
    } 
}


int main() 
{ 
  char filename[512]; 
  IplImage *src,*edge1,*edge2; 
  puts("File name:"); 
  gets(filename); 
  src = cvLoadImage(filename,CV_LOAD_IMAGE_GRAYSCALE ); 
  edge1=cvCloneImage(src); 
  edge2=cvCloneImage(src);

  cvNamedWindow("src", CV_WINDOW_AUTOSIZE); 
  cvMoveWindow("src", 100, 100); 
  cvShowImage( "src", src); 
  cvNamedWindow("Edge", CV_WINDOW_AUTOSIZE); 
  cvMoveWindow("Edge", 200, 100); 
  cvNamedWindow("EdgeOpenMP", CV_WINDOW_AUTOSIZE); 
  cvMoveWindow("EdgeOpenMP", 300, 100); 
  /* 以上都是准备一些窗口和图形基本数据 */

  int tekrar=100;//运行次数 
  int thresh=30; 
  double start, end,t1, t2; 
  
  /* 计算没有使用OpenMP优化的时间 */ 
  start= (double)cvGetTickCount();//记下开始的时钟计数，以便计算函数或用户代码执行时间 
  for(int i=0;i<tekrar;i++) 
    Edge(src,edge1,thresh); 
  end= (double)cvGetTickCount();//记下结束的时钟计数 
  t1= (end-start)/((double)cvGetTickFrequency()*1000.);//计算运行时间，以毫秒为单位 
  printf( "Run time without OpenMP = %g ms\n", t1 );

  /* 计算使用了OpenMP优化的时间 */ 
  start= (double)cvGetTickCount(); 
  for(int i=0;i<tekrar;i++) 
    EdgeOpenMP(src,edge2,thresh); 
  end= (double)cvGetTickCount(); 
  t2= (end-start)/((double)cvGetTickFrequency()*1000.); 
  printf( "Run time with OpenMP = %g ms\n", t2 );

  printf( "Performance ratio (%%) = %% %.1f \n", 100*(t1/t2-1) );

  cvShowImage( "Edge", edge1); 
  cvShowImage( "EdgeOpenMP", edge2); 
  cvWaitKey(); 
  cvDestroyWindow("Edge"); 
  cvDestroyWindow("EdgeOpenMP"); 
  cvReleaseImage(&src); 
  cvReleaseImage(&edge1); 
  cvReleaseImage(&edge2); 
}

这是我的结果：


这里的测试结果：
http://blog.csdn.net/augusdi/article/details/8808226
  在cpp文件中添加如下代码：

#include "stdafx.h"

#include<omp.h>

#include<iostream>

usingnamespace std;


//循环测试函数
void test()
{
for(int i=0;i<10000;i++)
{

}
}


int _tmain(int argc,_TCHAR* argv[])
{
cout<<"这是一个串行测试程序!\n";
double start = omp_get_wtime( );//获取起始时间

for(int i = 0; i < 10000; i++)
{ 
test();
}

double end = omp_get_wtime( );

cout<<"计算耗时为："<<end -start<<"\n";

cin>>end;

return 0;
}

#include "stdafx.h"

#include<omp.h>

#include <iostream>

using namespace std;


//循环测试函数
void test()
{
for(inti=0;i<10000;i++)
{

}
}

int _tmain(int argc, _TCHAR* argv[])
{
cout<<"这是一个并行测试程序!\n";

doublestart = omp_get_wtime( );//获取起始时间


#pragma ompparallel for
for(inti = 0; i < 10000; i++) 
{
test();
}


doubleend = omp_get_wtime( );

cout<<"计算耗时为："<<end -start<<"\n";

cin>>end;

return0;
}