opencv之基于颜色的对象跟踪和过滤

注:此教程是对贾志刚老师的opencv课程学习的一个记录,在此表示对贾老师的感谢.
基于颜色的对象跟踪和过滤步骤如下：
１.inRange过滤
2. 形态学操作提取
3. 轮廓查找
4. 外接矩形获取
5. 位置标定

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

Rect roi;

void processFrame(Mat &binary, Rect &rect);

int main(int argc, char** argv) {
    
    
	// load video
	VideoCapture capture;
	capture.open("/home/fuhong/code/cpp/opencv_learning/src/object_tracing/video/video_006.mp4");
	if (!capture.isOpened()) {
    
    
		printf("could not find video file");
		return -1;
	}

	Mat frame, mask;
	Mat kernel1 = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
	Mat kernel2 = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1));

	namedWindow("input video", CV_WINDOW_AUTOSIZE);
	namedWindow("track mask", CV_WINDOW_AUTOSIZE);
	while (capture.read(frame)) {
    
    
	    //inrange()函数:提取两个像素值范围内的像素点
		inRange(frame, Scalar(0, 127, 0), Scalar(120, 255, 120), mask);
		morphologyEx(mask, mask, MORPH_OPEN, kernel1, Point(-1, -1), 1);   //开操作，可以去掉小的对象，假设对象是前景色，背景是黑色
		dilate(mask, mask, kernel2, Point(-1, -1), 4);                     //膨胀操作
		imshow("track mask", mask);

		processFrame(mask, roi);
		rectangle(frame, roi, Scalar(0, 0, 255), 3, 8, 0);
		imshow("input video", frame);

		// trigger exit
		char c = waitKey(100);
		if (c == 27) {
    
    
			break;
		}
	}

	capture.release();     //释放资源
	waitKey(0);
	return 0;
}


/*!
 * @note .作用: 从所有的轮廓中找出面积最大的轮廓所在的boundingRect包围矩形。
 * @param binary : 二值化图像
 * @param rect  ： 感兴趣区域
 */
void processFrame(Mat &binary, Rect &rect) {
    
    
	vector<vector<Point>> contours;
	vector<Vec4i> hireachy;
	findContours(binary, contours, hireachy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
	if (contours.size() > 0) {
    
    
		double maxArea = 0.0;
		for (size_t t = 0; t < contours.size(); t++) {
    
    
			double area = contourArea(contours[static_cast<int>(t)]);
			if (area > maxArea) {
    
    
				maxArea = area;
				rect = boundingRect(contours[static_cast<int>(t)]);
			}
		}
	}
	else {
    
    
		rect.x = rect.y = rect.width = rect.height = 0;
	}

}

效果如下：