opencv 图像帧差法（图像相减） 代码

方法一：

#include<stdio.h>#include<stdlib.h>#include<math.h>#include "cv.h"#include "highgui.h"IplImage * img0=NULL;IplImage * img1=NULL;IplImage * img2=NULL;void onTrackerSlid(int pos){  int i,j;CvScalar s0,s1,s2;for(i=0;i<img0->height;i++)for(j=0;j<img0->width;j++){s0=cvGet2D(img0,i,j); // get the (i,j) pixel values1=cvGet2D(img1,i,j);s2=cvGet2D(img2,i,j);// for(k=0;k<channel;k++)if(fabs(s1.val[0]-s0.val[0])>pos){s2.val[0]=0;cvSet2D(img2,i,j,s2); // set the (i,j) pixel value}else{s2.val[0]=255;cvSet2D(img2,i,j,s2); }}cvShowImage( "result", img2 );}int main( int argc, char** argv ){    int thresh = 80;//载入图像img0=cvLoadImage("c:\\line110.jpg",0);//不可以再一次用IplImage定义，因为其已经是全局变量img1=cvLoadImage("c:\\line111.jpg",0);img2=cvCreateImage(cvGetSize(img0),8,1);// int channel = img->nChannels;// printf("the image is %d X %d wiht %d channels",height,width,channel);cvNamedWindow( "imge0", CV_WINDOW_AUTOSIZE);//创建窗口cvNamedWindow( "imge1", CV_WINDOW_AUTOSIZE);cvNamedWindow( "result", CV_WINDOW_AUTOSIZE);cvShowImage( "imge0", img0 );//显示图像cvShowImage( "imge1", img1 );cvCreateTrackbar("threshold","result",&thresh,255,onTrackerSlid);onTrackerSlid(thresh);cvWaitKey(0); //等待按键cvDestroyWindow( "Imge0" );//销毁窗口cvDestroyWindow( "Imge1" );cvDestroyWindow( "result" );cvReleaseImage( &img0); //释放图像cvReleaseImage( &img1);cvReleaseImage( &img2);return -1;}

结果 ：

方法二：

#include<stdio.h>#include<stdlib.h>#include<math.h>#include "cv.h"#include "highgui.h"IplImage * img0=NULL;IplImage * img1=NULL;IplImage * img2=NULL;uchar *data0=NULL;uchar *data1=NULL;uchar *data2=NULL;void onTrackerSlid(int pos){int i,j;int     height = img0->height;int width   = img0->width;int step    = img0->widthStep/sizeof(uchar);data0   = (uchar*)img0->imageData;data1   = (uchar*)img1->imageData;data2   = (uchar*)img2->imageData;for(i=0;i<height;i++) for(j=0;j<width;j++){if(abs( data1[i*step+j+0]-data0[i*step+j+0])>pos)data2[i*step+j+0] =255;elsedata2[i*step+j+0] = 0;}cvShowImage( "result", img2 );}// 说明：对于这一部分可以利用cv自带的函数实现图像相减和阈值处理，方法是：// 增加一个IplImage 对象img3，并使用cvCreateImage将其初始化，将此部分换成如下代码：// cvAbsDiff(img1, img0, img2);//图像相减功能和使用 if(( data1[i*step+j+0]-data0[i*step+j+0])>pos)是一样的，没取绝对值// cvThreshold(img2, img3, pos, 255, CV_THRESH_BINARY);//阈值处理// cvShowImage( "result", img3 );//显示处理后的图像图像int main( int argc, char** argv ){    int thresh = 80;//载入图像// img0=cvLoadImage(argv[1],0);// img1=cvLoadImage(argv[2],0);// img2=cvCreateImage(cvGetSize(img0),8,1);img0=cvLoadImage("c:\\line110.jpg",0);//不可以再一次用IplImage定义，因为其已经是全局变量img1=cvLoadImage("c:\\line111.jpg",0);img2=cvCreateImage(cvGetSize(img0),8,1);cvSmooth(img0, img0, CV_GAUSSIAN, 3, 0, 0,0);//高斯滤波平滑图像// int channel = img->nChannels;// printf("the image is %d X %d wiht %d channels",height,width,channel);cvNamedWindow( "imge0", CV_WINDOW_AUTOSIZE);//创建窗口cvNamedWindow( "imge1", CV_WINDOW_AUTOSIZE);cvNamedWindow( "result", CV_WINDOW_AUTOSIZE);cvShowImage( "imge0", img0 );//显示图像cvShowImage( "imge1", img1 );cvCreateTrackbar("threshold","result",&thresh,255,onTrackerSlid);onTrackerSlid(thresh);cvWaitKey(0); //等待按键cvDestroyWindow( "Imge0" );//销毁窗口cvDestroyWindow( "Imge1" );cvDestroyWindow( "result" );cvReleaseImage( &img0); //释放图像cvReleaseImage( &img1);cvReleaseImage( &img2);return -1;}

结果：

方法三：

/*使用矩阵减法做图像帧差，其代码如下，和使用cv自带的函数差不多*/#include<stdio.h>#include<stdlib.h>#include<math.h>#include "cv.h"#include "highgui.h"IplImage * img0=NULL;IplImage * img1=NULL;CvMat * img2=NULL;CvMat *img3=NULL;void onTrackerSlid(int pos){cvSub(img0, img1, img2,0);//图像相减cvThreshold(img2, img3, pos, 255,0 CV_THRESH_BINARY);//阈值处理cvShowImage( "result", img3 );//显示处理后的图像图像}int main( int argc, char** argv ){    int thresh = 80;//载入图像img0=cvLoadImage("c:\\line110.jpg",0);//不可以再一次用IplImage定义，因为其已经是全局变量img1=cvLoadImage("c:\\line111.jpg",0);img2=cvCreateMat(img0->height,img0->width,CV_8UC1);//矩阵指针的初始化，与cvCreareImage类似img3=cvCreateMat(img0->height,img0->width,CV_8UC1);cvSmooth(img0, img0, CV_GAUSSIAN, 3, 0, 0,0);//高斯滤波平滑图像cvNamedWindow( "imge0", CV_WINDOW_AUTOSIZE);//创建窗口cvNamedWindow( "imge1", CV_WINDOW_AUTOSIZE);cvNamedWindow( "result", CV_WINDOW_AUTOSIZE);cvShowImage( "imge0", img0 );//显示图像cvShowImage( "imge1", img1 );cvCreateTrackbar("threshold","result",&thresh,255,onTrackerSlid);onTrackerSlid(thresh);cvWaitKey(0); //等待按键cvDestroyWindow( "Imge0" );//销毁窗口cvDestroyWindow( "Imge1" );cvDestroyWindow( "result" );cvReleaseImage( &img0); //释放图像cvReleaseImage( &img1);cvReleaseMat( &img2);cvReleaseMat( &img3);return -1;}

结果：