opencv中的轮廓检测与位置标定

opencv中的轮廓检测与位置标定

步骤是灰度化、二值化、寻找轮廓、最小外接矩形、图像调整。
比较简单，欢迎探讨，下面是代码

int main()
{
	Mat srcImage = imread("D://test1.jpg");
	Mat srcGray, threImage,dstImage;

	cvtColor(srcImage, srcGray, CV_RGB2GRAY);
	imshow("srcImage", srcImage);
	threshold(srcGray, threImage, 130, 255, 0);
	//imshow("threshold", threImage);
	dstImage = threImage < 100;//反色
	//imshow("reverse", dstImage);
	
	std::vector<Point> contours;
	std::vector<std::vector<cv::Point>> f_contours;
	cv::findContours(dstImage,f_contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE); 
	
	//找到目标轮廓
	int max_area = 0;
	int index;
	for (int i = 0; i < f_contours.size(); i++)
	{
		double tmparea = fabs(contourArea(f_contours[i]));
		if (tmparea > max_area)
		{
			index = i;
			max_area = tmparea;
		}

	}
	Mat box_contours(dstImage.size(), CV_8U,Scalar(0));
	contours = f_contours[index];
    
    //显示轮廓
	Mat contoursMat(dstImage.size(), CV_8U, Scalar(0));
	for (int i = 0; i < contours.size(); i++)
	{
		circle(contoursMat, contours[i], 3, Scalar(255, 0, 0), -1);
	}
	imshow("contours", contoursMat);

	//获得最小矩形
	RotatedRect box = minAreaRect(Mat(contours));
	Point2f center, vtx[4];
	box.points(vtx);
	for (int i = 0; i < 4; i++)
	{
		line(box_contours, vtx[i], vtx[(i + 1) % 4], Scalar(255, 0, 0), 1, CV_AA);
	}

	cv::imshow("Contoursbox", box_contours);
	Mat warpMat(Size(2, 3), CV_32F);
	warpMat = getRotationMatrix2D(vtx[1], box.angle, 1);
	warpAffine(srcImage, dstImage, warpMat, dstImage.size());
	
	float x, y;//旋转后的坐标
	x = vtx[1].x*cos(box.angle) - vtx[1].y*sin(box.angle);
	y= vtx[1].x*sin(box.angle) + vtx[1].y*cos(box.angle);
	//定义平移矩阵
	cv::Mat t_mat = cv::Mat::zeros(2, 3, CV_32FC1);
	t_mat.at<float>(0, 0) = 1;
	t_mat.at<float>(0, 2) = 100-x; //水平平移量
	t_mat.at<float>(1, 1) = 1;
	t_mat.at<float>(1, 2) = 100-y; //竖直平移量

	//根据平移矩阵进行仿射变换
	cv::warpAffine(dstImage, dstImage, t_mat, dstImage.size());
	
	imshow("warp", dstImage);
	waitKey(100000);
	
	return 0;
}

图一为原图，图二为识别轮廓，图三为最小外接矩形，图四为将矩形左上角调整至（100,100）的效果图