OpenCV——对象提取

文章目录[隐藏]

解决思路
代码实现

对象提取，简而言之就是获取指定图像，去除其他图像.

解决思路

二值处理 + 形态学处理（开运算+闭运算，轮廓发现） + 横纵比过滤计算 .

代码实现

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

using  namespace cv;
using  namespace std;

Mat src, binary, close_dst,open_dst;
int main(int argc, char** argv)
{
	src = imread("D:/test/object.png", 0);
	if (src.empty())
	{
		cout << "图片未找到！！！" << endl;
		return -1;
	}
	imshow("input image", src);

	//二值化操作
	threshold(src, binary, 0, 255, THRESH_BINARY | THRESH_OTSU);
	bitwise_not(binary, binary, Mat());
	imshow("binary image",binary);

	/*---------------------形态学操作-------------------------*/
	Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));

	//闭操作，把中间的细小点联通起来
	morphologyEx(binary, close_dst, MORPH_CLOSE, kernel, Point(-1, -1));
	imshow("close image", close_dst);

	//开操作，去除多余的点
	kernel = getStructuringElement(MORPH_RECT, Size(7, 7), Point(-1, -1));
	morphologyEx(binary, open_dst, MORPH_OPEN, kernel, Point(-1, -1));
	imshow("open image", open_dst);

	/*---------------------获取对象轮廓-------------------------*/
	Mat dst = Mat::zeros(src.size(), CV_8UC3);
	vector <vector<Point>> contours;
	vector<Vec4i> hierachy;
	findContours(open_dst, contours, hierachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
	Point cc;
	Mat result_img = src.clone();
	cvtColor(result_img, result_img, CV_GRAY2BGR);

	//RNG rng((int)time(0));
	for (size_t t = 0; t < contours.size(); t++)
	{

		double area = contourArea(contours[t]);//获取每个轮廓围成的面积
		if (area < 100)  //如果轮廓围成的面积小于100，则过滤
			continue;
		//横纵比过滤
		Rect rect = boundingRect(contours[t]);//用最小的外接矩形把对象给包起来

		//因为检测提取的对象是圆，所以横纵比可以设定为在0.9-1.2之间
		float h_w = (float)rect.height / rect.width;
		if (h_w > 0.9&&h_w < 1.2)
		{
		drawContours(dst, contours, static_cast<int>(t), Scalar(0, 0, 255), 2, 8, Mat(), 0, Point(0, 0));
		double length = arcLength(contours[t], true);//周长
		printf("面积:%f\n",area);
		printf("周长:%f\n", length);

		/*----------------获取圆点坐标----------------------*/
		
		int x = rect.x + rect.width / 2;//rect.x是矩形左上角的横坐标
		int y = rect.y + rect.height / 2;//rect.y是矩形左上角的纵坐标
		cc = Point(x, y);
		//Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
		circle(result_img, cc, 2, Scalar(0,0,255), 2, 8, 0);

		}
	}
	imshow("contours image", dst);
	imshow("result image", result_img);
	waitKey(0);
	return 0;
}