OpenCV 【二十六】計算物體的凸包/創建包圍輪廓的矩形和圓形邊界框

目錄

topic 1:模板匹配

topic 2:圖像中尋找輪廓

topic 3:計算物體的凸包

topic 4:輪廓創建可傾斜的邊界框和橢圓¶

 

3.1 目標

3.2 代碼實例1

3.3 代碼實例2

3.4 實例3運行結果

3.5 運行結果

---

topic 1:模板匹配

topic 2:圖像中尋找輪廓

topic 3:計算物體的凸包

topic 4:輪廓創建可傾斜的邊界框和橢圓¶

topic 5:輪廓矩¶

目錄

---

 

3.1 目標

• 使用OpenCV函數 convexHull

3.2 代碼實例1

//src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\4.jpg", 1);
​
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
​
using namespace cv;
using namespace std;
​
Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);
​
/// Function header
void thresh_callback(int, void*);
​
/** @function main */
int main(int argc, char** argv)
{
    /// 加載源圖像
    src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);
​
    /// 轉成灰度圖並進行模糊降噪
    cvtColor(src, src_gray, CV_BGR2GRAY);
    blur(src_gray, src_gray, Size(3, 3));
​
    /// 創建窗體
    char* source_window = "Source";
    namedWindow(source_window, CV_WINDOW_AUTOSIZE);
    imshow(source_window, src);
​
    createTrackbar(" Threshold:", "Source", &thresh, max_thresh, thresh_callback);
    thresh_callback(0, 0);
​
    waitKey(0);
    return(0);
}
​
/** @function thresh_callback */
void thresh_callback(int, void*)
{
    Mat src_copy = src.clone();
    Mat threshold_output;
    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;
​
    /// 對圖像進行二值化
    threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);
​
    /// 尋找輪廓
    findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
​
    /// 對每個輪廓計算其凸包
    vector<vector<Point> >hull(contours.size());
    for (int i = 0; i < contours.size(); i++)
    {
        convexHull(Mat(contours[i]), hull[i], false);
    }
​
    /// 繪出輪廓及其凸包
    Mat drawing = Mat::zeros(threshold_output.size(), CV_8UC3);
    for (int i = 0; i< contours.size(); i++)
    {
        Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
        drawContours(drawing, contours, i, color, 1, 8, vector<Vec4i>(), 0, Point());
        drawContours(drawing, hull, i, color, 1, 8, vector<Vec4i>(), 0, Point());
    }
​
    /// 把結果顯示在窗體
    namedWindow("Hull demo", CV_WINDOW_AUTOSIZE);
    imshow("Hull demo", drawing);
}

3.3 代碼實例2

//src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\4.jpg", 1);
​
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
​
using namespace cv;
using namespace std;
​
Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);
​
/// 函數聲明
void thresh_callback(int, void*);
​
/** @主函數 */
int main(int argc, char** argv)
{
    /// 載入原圖像, 返回3通道圖像
    src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);
​
    /// 轉化成灰度圖像並進行平滑
    cvtColor(src, src_gray, CV_BGR2GRAY);
    blur(src_gray, src_gray, Size(3, 3));
​
    /// 創建窗口
    char* source_window = "Source";
    namedWindow(source_window, CV_WINDOW_AUTOSIZE);
    imshow(source_window, src);
​
    createTrackbar(" Threshold:", "Source", &thresh, max_thresh, thresh_callback);
    thresh_callback(0, 0);
​
    waitKey(0);
    return(0);
}
​
/** @thresh_callback 函數 */
void thresh_callback(int, void*)
{
    Mat threshold_output;
    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;
​
    /// 使用Threshold檢測邊緣
    threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);
    /// 找到輪廓
    findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
​
    /// 多邊形逼近輪廓 + 獲取矩形和圓形邊界框
    vector<vector<Point> > contours_poly(contours.size());
    vector<Rect> boundRect(contours.size());
    vector<Point2f>center(contours.size());
    vector<float>radius(contours.size());
​
    for (int i = 0; i < contours.size(); i++)
    {
        approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
        boundRect[i] = boundingRect(Mat(contours_poly[i]));
        minEnclosingCircle(contours_poly[i], center[i], radius[i]);
    }
​
​
    /// 畫多邊形輪廓 + 包圍的矩形框 + 圓形框
    Mat drawing = Mat::zeros(threshold_output.size(), CV_8UC3);
    for (int i = 0; i< contours.size(); i++)
    {
        Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
        drawContours(drawing, contours_poly, i, color, 1, 8, vector<Vec4i>(), 0, Point());
        rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0);
        circle(drawing, center[i], (int)radius[i], color, 2, 8, 0);
    }
​
    /// 顯示在一個窗口
    namedWindow("Contours", CV_WINDOW_AUTOSIZE);
    imshow("Contours", drawing);
}

3.4 實例3運行結果

//src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\4.jpg", 1);

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

/// 函數聲明
void thresh_callback(int, void*);

/** @主函數 */
int main(int argc, char** argv)
{
	/// 讀入原圖像, 返回3通道圖像數據
	src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);

	/// 把原圖像轉化成灰度圖像並進行平滑
	cvtColor(src, src_gray, CV_BGR2GRAY);
	blur(src_gray, src_gray, Size(3, 3));

	/// 創建新窗口
	char* source_window = "Source";
	namedWindow(source_window, CV_WINDOW_AUTOSIZE);
	imshow(source_window, src);

	createTrackbar(" Canny thresh:", "Source", &thresh, max_thresh, thresh_callback);
	thresh_callback(0, 0);

	waitKey(0);
	return(0);
}

/** @thresh_callback 函數 */
void thresh_callback(int, void*)
{
	Mat canny_output;
	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;

	/// 使用Canndy檢測邊緣
	Canny(src_gray, canny_output, thresh, thresh * 2, 3);
	/// 找到輪廓
	findContours(canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));

	/// 計算矩
	vector<Moments> mu(contours.size());
	for (int i = 0; i < contours.size(); i++)
	{
		mu[i] = moments(contours[i], false);
	}

	///  計算中心矩:
	vector<Point2f> mc(contours.size());
	for (int i = 0; i < contours.size(); i++)
	{
		mc[i] = Point2f(mu[i].m10 / mu[i].m00, mu[i].m01 / mu[i].m00);
	}

	/// 繪製輪廓
	Mat drawing = Mat::zeros(canny_output.size(), CV_8UC3);
	for (int i = 0; i< contours.size(); i++)
	{
		Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
		drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
		circle(drawing, mc[i], 4, color, -1, 8, 0);
	}

	/// 顯示到窗口中
	namedWindow("Contours", CV_WINDOW_AUTOSIZE);
	imshow("Contours", drawing);

	/// 通過m00計算輪廓面積並且和OpenCV函數比較
	printf("\t Info: Area and Contour Length \n");
	for (int i = 0; i< contours.size(); i++)
	{
		printf(" * Contour[%d] - Area (M_00) = %.2f - Area OpenCV: %.2f - Length: %.2f \n", i, mu[i].m00, contourArea(contours[i]), arcLength(contours[i], true));
		Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
		drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
		circle(drawing, mc[i], 4, color, -1, 8, 0);
	}
}

3.5 運行結果

實例1運行結果

 

實例2運行結果

實例3運行結果