//---------------------------------【標頭檔案、名稱空間包含部分】----------------------------
//		描述：包含程式所使用的標頭檔案和名稱空間
//------------------------------------------------------------------------------------------------
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;


//-----------------------------------【巨集定義部分】-------------------------------------------- 
//		描述：定義一些輔助巨集 
//------------------------------------------------------------------------------------------------ 
#define WINDOW_NAME1 "【原始圖】"					//為視窗標題定義的巨集 
#define WINDOW_NAME2 "【影象外界矩形輪廓】"        //為視窗標題定義的巨集 
#define WINDOW_NAME3 "【輪廓提取影象】" 

//-----------------------------------【全域性變數宣告部分】--------------------------------------
//		描述：全域性變數的宣告
//-----------------------------------------------------------------------------------------------
Mat g_srcImage; Mat g_grayImage;
RNG g_rng(12345);
Mat g_cannyMat_output;
vector<vector<Point> > g_vContours;
vector<Vec4i> g_vHierarchy;
vector<Point> contour;
int g_nThick = 0;
Scalar color;
Mat dst = Mat::zeros(g_cannyMat_output.rows, g_cannyMat_output.cols, CV_8UC3);
vector<vector<Point> > contours_poly(g_vContours.size());
//-----------------------------------【全域性變數宣告部分】--------------------------------------
//		描述：全域性變數的宣告
//-----------------------------------------------------------------------------------------------
void on_ThreshChange(int, void*);

//-----------------------------------【main( )函式】--------------------------------------------
//		描述：控制檯應用程式的入口函式，我們的程式從這裡開始執行
//-----------------------------------------------------------------------------------------------
int main(int argc, char** argv)
{
	//【0】改變console字型顏色
	system("color 9F");

	// 讀入原影象, 返回3通道影象資料
	g_srcImage = imread("32.jpg", 1);
	if (!g_srcImage.data) { printf("讀取圖片錯誤，請確定目錄下是否有imread函式指定圖片存在~！ \n"); return false; }

	imshow(WINDOW_NAME1, g_srcImage);
	imwrite("原始圖.jpg", g_srcImage);
 

	// 把原影象轉化成灰度影象並進行平滑
	cvtColor(g_srcImage, g_grayImage, COLOR_BGR2GRAY);
	//二值化
	threshold(g_grayImage, g_grayImage, 145, 255, 1);
	//imshow("二值化", g_grayImage);
	//imwrite("二值化.jpg", g_grayImage);

	//膨脹操作
	Mat element = getStructuringElement(MORPH_RECT, Size(3, 3)); erode(g_grayImage, g_grayImage, element);
	dilate(g_grayImage, g_grayImage, element);
	dilate(g_grayImage, g_grayImage, element);
	dilate(g_grayImage, g_grayImage, element);
 

       //去噪操作
	blur(g_grayImage, g_grayImage, Size(3, 3));

	imshow("腐膨", g_grayImage);
	//呼叫on_ThreshChange函式
	on_ThreshChange(0, 0);

	waitKey(0);
	return(0);
}


//-----------------------------------【on_ThreshChange( )函式】-------------------------------
//		描述：回撥函式
//-----------------------------------------------------------------------------------------------
void on_ThreshChange(int, void*)

{
	// 使用Canndy檢測邊緣
	Canny(g_grayImage, g_cannyMat_output, 150, 255, 3);
	namedWindow("邊緣檢測", WINDOW_AUTOSIZE);
	imshow("邊緣檢測", g_cannyMat_output);
	//	imwrite("最終輪廓.jpg", g_cannyMat_output);
	Mat dst = Mat::zeros(g_cannyMat_output.rows, g_cannyMat_output.cols, CV_8UC3);
	// 找到輪廓
	findContours(g_cannyMat_output, g_vContours, g_vHierarchy, RETR_EXTERNAL, CHAIN_APPROX_NONE, Point(0, 0));
	int m = g_vContours.size();//得到輪廓的數量  
	int n = 0;

	vector<RotatedRect> minRect(g_vContours.size());
	Mat DstImg;
	for (int i = 0; i < m; ++i)
	{
		n = g_vContours[i].size();
		for (int j = 0; j<n; ++j)
		{
			contour.push_back(g_vContours[i][j]);//讀取每個輪廓的點  
		}
		double Length = arcLength(g_vContours[i], true); //取得輪廓周長

		minRect[i] = minAreaRect(Mat(g_vContours[i]));

		if (Length>1000 && Length < 1200)//只畫出符合周長範圍的輪廓 
		{
			Scalar color(255, 255, 255);

			drawContours(dst, g_vContours, i, color, 1, 8, g_vHierarchy);//繪製輪廓

			Point2f rect_points[4]; minRect[i].points(rect_points);

		/*	for (int j = 0; j < 4; j++)
			{
				line(dst, rect_points[j], rect_points[(j + 1) % 4], color, 1, 8);
				
			}*/

			CvPoint2D32f rectpoints[4];
			cvBoxPoints(minRect[i], rectpoints);
			
			cout << "angle:\n" << (float)minRect[i].angle << endl;//輸出角度
			cout << "center:\n" << minRect[i].center << endl;//輸出外接矩形的中心
			cout << "size:\n" << minRect[i].size << endl;//矩形的寬和高
			cout << "(x0,y0):\n" << rect_points[0] << endl;//獲取矩形的四個點
			cout << "(x1,y1):\n" << rect_points[1] << endl;
			cout << "(x2,y2):\n" << rect_points[2] << endl;
			cout << "(x3,y3):\n" << rect_points[3] << endl;
			float a = rect_points[0].x;//獲取外接矩形的左上X座標的值
			float b = rect_points[0].y;
			float c = rect_points[1].x;
			float d = rect_points[1].y;
			float e = rect_points[2].x;
			float f = rect_points[2].y;
			float g = rect_points[3].x;
			float h = rect_points[3].y;
			float angle = minRect[i].angle;


			Rect brect = minRect[i].boundingRect();

			rectangle(g_srcImage, brect, Scalar(255, 0, 0));

			imshow(WINDOW_NAME2, g_srcImage);


		//	namedWindow("DstImg", 1);

			g_srcImage(brect).copyTo(DstImg);

			imwrite("DstImg.jpg", DstImg);

			imshow(WINDOW_NAME3, DstImg);



		}
		contour.clear();
	}

	namedWindow("src", 1);
	imshow("src", dst);
}
 

輸出的外接矩形資訊圖

符合周長範圍的輪廓

在原圖上標出最小外接矩形以及輸出最小外接矩形

根據 findContours 函式寫的一個小程式，可能有許多不到位的，期待大家批評指正，相互交流！