基于ROI的目标检测

最新推荐文章于 2025-03-05 16:57:58 发布

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最新推荐文章于 2025-03-05 16:57:58 发布 · 3.3k 阅读

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CC 4.0 BY-SA版权

本文探讨了如何利用Region of Interest (ROI) 技术进行高效的目标检测，介绍了ROI在不同场景下的应用及其优势。

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可用版：

#include "core/core.hpp"  
#include "highgui/highgui.hpp"  
#include "imgproc/imgproc.hpp"  
#include<iostream>  

using namespace cv;
using namespace std;

Mat frame;
Mat frameCopy; //绘制矩形框时用来拷贝原图的图像
bool leftButtonDownFlag = false; //左键单击后视频暂停播放的标志位
Point originalPoint; //矩形框起点
Point processPoint; //矩形框终点

//*******************************************************************//  
//鼠标回调函数  
void onMouse(int event, int x, int y, int flags, void *ustc)
{

	if (event == CV_EVENT_LBUTTONDOWN)
	{
		leftButtonDownFlag = true; //标志位
		originalPoint = Point(x, y);  //设置左键按下点的矩形起点
		processPoint = originalPoint;
	}
	if (event == CV_EVENT_MOUSEMOVE&&leftButtonDownFlag)
	{
		frameCopy = frame.clone();
		processPoint = Point(x, y);
		if (originalPoint != processPoint)
		{
			//在复制的图像上绘制矩形
			rectangle(frameCopy, originalPoint, processPoint, Scalar(255, 0, 0), 2);
		}
		imshow("Cap", frameCopy);
	}
	if (event == CV_EVENT_LBUTTONUP)
	{
		leftButtonDownFlag = false;
		Mat rectImage = frame(Rect(originalPoint, processPoint)); //子图像显示
		imshow("ROI", rectImage);
	}

}

Mat MoveDetect(Mat background, Mat img)
{
	//将background和img转为灰度图
	Mat result = img.clone();
	Mat gray1, gray2;
	cvtColor(background, gray1, CV_BGR2GRAY);
	cvtColor(img, gray2, CV_BGR2GRAY);

	//进行canny边缘检测 
	Canny(background, background, 0, 30, 3);

	//将background和img做差；对差值图diff进行阈值化处理
	Mat diff;
	absdiff(gray1, gray2, diff);
	//imshow("absdiss", diff);
	threshold(diff, diff, 50, 255, CV_THRESH_BINARY);
	//imshow("threshold", diff);

	/*
	//腐蚀膨胀消除噪音
	Mat element = getStructuringElement(MORPH_RECT, Size(3