简介
本篇使用opencv函数phaseCorrelate来计算video录像时候移动速度和方向或者说是摄像头当前移动速度和方向。
phaseCorrelate
Point2d phaseCorrelate(InputArray src1, InputArray src2, InputArray window=noArray())
src1:前一帧video图像;
src2:当前video图像;
window:浮点阵列的窗口系数，用来减少边缘效应(可选)。
返回的Point2d：返回的二维坐标，x表示src2相对于src1在X轴上移动的距离，y表示src2相对于src1在Y轴上移动的距离；
实例讲解
具体代码
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <stdio.h>
using namespace cv;
int main(int argc, char* argv[])
{
VideoCapture video(argv[1]);
Mat frame, curr, prev, curr64f, prev64f, hann;
int key = 0;
Mat imageROI;
CvFont font;
double hScale=1;
double vScale=1;
int lineWidth=1;
char showMsg[20];
cvInitFont(&font, CV_FONT_HERSHEY_PLAIN|CV_FONT_ITALIC, hScale,vScale,0,lineWidth);
do
{
video >> frame;
cvtColor(frame, curr, COLOR_RGB2GRAY);
if(prev.empty()){
prev = curr.clone();
createHanningWindow(hann, curr.size(), CV_64F);
}
if(curr.empty()){
break;
}
prev.convertTo(prev64f, CV_64F);
curr.convertTo(curr64f, CV_64F);
Point2d shift = phaseCorrelate(prev64f, curr64f, hann);
double radius = cv::sqrt(shift.x*shift.x + shift.y*shift.y);
if(radius > 5){
int width = curr.cols;
int height = curr.rows;
Point center(50, 40);
printf("radius:%lf\n", radius);
if((width < 100) && (height < 100)){
printf("image size is too small!!!\n");
break;
}
imageROI = frame(cv::Rect((width - 100), 5, 95, 100));
IplImage img = imageROI;
cvZero(&img);
circle(imageROI, center, (int)radius, cv::Scalar(0, 255, 0), 1, CV_AA);
line(imageROI, center, Point(center.x + (int)shift.x, center.y + (int)shift.y), cv::Scalar(0, 255, 0), 1, CV_AA);
sprintf(showMsg, "x:%d", -(int)shift.x);
cvPutText(&img, showMsg ,cvPoint(10,85),&font,CV_RGB(255,0,0));
sprintf(showMsg, "y:%d", -(int)shift.y);
cvPutText(&img, showMsg ,cvPoint(10,97),&font,CV_RGB(255,0,0));
}
imshow("phase shift", frame);
key = waitKey(20);
if(key == ‘q‘){
break;
}
prev = curr.clone();
} while((char)key != 27);
return 0;
}
代码讲解
1、首先用cvInitFont初始化字体显示，接着在一个循环中，不停的依次读取每帧video数据，然后将前一帧和当前帧数据，转化格式为CV_64F， 然后传入phaseCorrelate中进行处理，接着用sqrt计算出返回相对位移坐标shift的平方根radius，如果radius小于5，则表示移动距离太短。直接跳过 处理流程，然后显示出当前帧数据，最后注意用当前帧数据更新前一帧数据。
cvInitFont(&font, CV_FONT_HERSHEY_PLAIN|CV_FONT_ITALIC, hScale,vScale,0,lineWidth);
do
{
video >> frame;
cvtColor(frame, curr, COLOR_RGB2GRAY);
if(prev.empty()){
prev = curr.clone();
createHanningWindow(hann, curr.size(), CV_64F);
}
if(curr.empty()){
break;
}
prev.convertTo(prev64f, CV_64F);
curr.convertTo(curr64f, CV_64F);
Point2d shift = phaseCorrelate(prev64f, curr64f, hann);
double radius = cv::sqrt(shift.x*shift.x + shift.y*shift.y);
if(radius > 5){
............
}
imshow("phase shift", frame);
key = waitKey(20);
if(key == ‘q‘){
break;
}
prev = curr.clone();
} while((char)key != 27);
2、如果radius大于5，就在图像的右上角，用imageROI取一块100x100的矩形，接着在里面根据之前获得的位移坐标shift，画出一条直线和一个圆， 来表示当前移动的速度，接着在矩形框最下面，显示出X和Y上，相对移动的距离。
if(radius > 5){
int width = curr.cols;
int height = curr.rows;
Point center(50, 40);
printf("radius:%lf\n", radius);
if((width < 100) && (height < 100)){
printf("image size is too small!!!\n");
break;
}
imageROI = frame(cv::Rect((width - 100), 5, 95, 100));
IplImage img = imageROI;
cvZero(&img);
circle(imageROI, center, (int)radius, cv::Scalar(0, 255, 0), 1, CV_AA);
line(imageROI, center, Point(center.x + (int)shift.x, center.y + (int)shift.y), cv::Scalar(0, 255, 0), 1, CV_AA);
sprintf(showMsg, "x:%d", -(int)shift.x);
cvPutText(&img, showMsg ,cvPoint(10,85),&font,CV_RGB(255,0,0));
sprintf(showMsg, "y:%d", -(int)shift.y);
cvPutText(&img, showMsg ,cvPoint(10,97),&font,CV_RGB(255,0,0));
}
效果演示
对应的效果演示如下:
时间： 2024-10-16 16:48:38