【opencv】检测形状

1.图片预处理，提取边界


经过处理后的图片轮廓更加清晰。更有利于后续的操作。

2.findContours（）查找轮廓，drawContours（）画出轮廓

3.contourArea（）计算每个轮廓的面积，通过if（area>2000）筛选出图形后再画出轮廓


通过面积大小，将噪声过滤

下面见代码示例：

#include
#include

using namespace std;
using namespace cv;

void getContours(Mat imgDil, Mat img)
{
	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;
    //找轮廓
	findContours(imgDil, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
	//drawContours(img, contours, -1, Scalar(255, 0, 255), 2);//-1画出所有轮廓

	vector<vector<Point>> conPoly(contours.size());
	vector<Rect> boundRect(contours.size());
	string objectType;
	for (int i = 0; i < contours.size(); i++)
	{
		//取出每个轮廓的面积
		int area = contourArea(contours[i]);
		cout << area << endl;
		//过滤小面积
		if (area > 2000)
		{
			float peri = arcLength(contours[i], true);
			approxPolyDP(contours[i], conPoly[i], 0.02*peri, true);
            //画出轮廓
			drawContours(img, conPoly, i, Scalar(255, 0, 255), 3);
			cout << conPoly[i].size() << endl;

			boundRect[i] = boundingRect(conPoly[i]);
			rectangle(img, boundRect[i].tl(), boundRect[i].br(), Scalar(0, 255, 0), 3);

			int objCor = (int)conPoly[i].size();
			if (objCor == 3)
			{
				objectType = "Tri";
			}
			else if (objCor == 4)
			{
				float aspRatio = (float)boundRect[i].width / (float)boundRect[i].height;
				if (aspRatio > 0.95 && aspRatio < 1.05)
				{
					objectType = "Square";
				}
				else
				{
					objectType = "Rect";
				}
				cout << aspRatio << endl;
			}
			else if (objCor > 4)
			{
				objectType = "Circle";
			}
			putText(img, objectType, { boundRect[i].x,boundRect[i].y - 5 }, FONT_HERSHEY_DUPLEX, 0.7, Scalar(0, 69, 255), 1);
		}
	}
}

int main()
{
	Mat img = imread("D:\\photogallery\\其他\\颜色卡.jpg");
	Mat imgGray, imgBlur,imgCanny,imgDil;
	//图片预处理
	resize(img, img, Size(), 0.8, 0.8);
	cvtColor(img, imgGray, COLOR_BGR2GRAY);
	GaussianBlur(imgGray, imgBlur, Size(3, 3), 0, 0);
	Canny(imgBlur, imgCanny, 25, 75);
	Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));
	dilate(imgCanny, imgDil, kernel);

	getContours(imgDil,img);

	imshow("img", img);
	imshow("imggray", imgGray);
	imshow("imgblur", imgBlur);
	imshow("imgcanny", imgCanny);
	imshow("imgdil", imgDil);

	waitKey(0);
	return 0;
}

运行结果：