OpenCV学习——OpenMP并行化实例

最新推荐文章于 2024-12-05 11:07:34 发布

最新推荐文章于 2024-12-05 11:07:34 发布 · 121 阅读

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本文介绍了一种利用OpenMP并行计算库优化图像边缘检测算法的方法。通过对比使用与未使用OpenMP的情况，展示了并行计算带来的性能提升。实验结果显示，在相同的图像处理任务中，采用OpenMP优化后的算法运行时间减少了约43%。

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

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：
File name:
dog.jpg
Run time without OpenMP = 647.627 ms
Run time with OpenMP = 453.001 ms
Performance ratio (%) = % 43.0