【OpenCV 】计算物体的凸包/创建包围轮廓的矩形和圆形边界框/createTrackbar添加滑动条/

topic 1:模板匹配

topic 2:图像中寻找轮廓

topic 3:计算物体的凸包

topic 4:轮廓创建可倾斜的边界框和椭圆¶

topic 5:轮廓矩¶

topic 6:为程序界面添加滑动条¶

3.1 目标

3.2 代码实例1

3.3 代码实例2

3.4 实例3运行结果

3.5 运行结果

topic 1:模板匹配

topic 2:图像中寻找轮廓

topic 3:计算物体的凸包

topic 4:轮廓创建可倾斜的边界框和椭圆¶

topic 5:轮廓矩¶

topic 6:为程序界面添加滑动条¶

3.1 目标

使用OpenCV函数 convexHull

3.2 代码实例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)
{/// 加载源图像src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);
/// 转成灰度图并进行模糊降噪cvtColor(src, src_gray, CV_BGR2GRAY);blur(src_gray, src_gray, Size(3, 3));
/// 创建窗体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;
/// 对图像进行二值化threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);
/// 寻找轮廓findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
/// 对每个轮廓计算其凸包vector<vector<Point> >hull(contours.size());for (int i = 0; i < contours.size(); i++){convexHull(Mat(contours[i]), hull[i], false);}
/// 绘出轮廓及其凸包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());}
/// 把结果显示在窗体namedWindow("Hull demo", CV_WINDOW_AUTOSIZE);imshow("Hull demo", drawing);
}

3.3 代码实例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);

/// 函数声明
void thresh_callback(int, void*);

/** @主函数 */
int main(int argc, char** argv)
{/// 载入原图像, 返回3通道图像src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);
/// 转化成灰度图像并进行平滑cvtColor(src, src_gray, CV_BGR2GRAY);blur(src_gray, src_gray, Size(3, 3));
/// 创建窗口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 函数 */
void thresh_callback(int, void*)
{Mat threshold_output;vector<vector<Point> > contours;vector<Vec4i> hierarchy;
/// 使用Threshold检测边缘threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);/// 找到轮廓findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
/// 多边形逼近轮廓 + 获取矩形和圆形边界框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]);}

/// 画多边形轮廓 + 包围的矩形框 + 圆形框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);}
/// 显示在一个窗口namedWindow("Contours", CV_WINDOW_AUTOSIZE);imshow("Contours", drawing);
}

3.4 实例3运行结果

//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);/// 函数声明
void thresh_callback(int, void*);/** @主函数 */
int main(int argc, char** argv)
{/// 读入原图像, 返回3通道图像数据src = imread("C:\\Users\\guoqi\\Desktop\\ch7\\15.jpg", 1);/// 把原图像转化成灰度图像并进行平滑cvtColor(src, src_gray, CV_BGR2GRAY);blur(src_gray, src_gray, Size(3, 3));/// 创建新窗口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 函数 */
void thresh_callback(int, void*)
{Mat canny_output;vector<vector<Point> > contours;vector<Vec4i> hierarchy;/// 使用Canndy检测边缘Canny(src_gray, canny_output, thresh, thresh * 2, 3);/// 找到轮廓findContours(canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));/// 计算矩vector<Moments> mu(contours.size());for (int i = 0; i < contours.size(); i++){mu[i] = moments(contours[i], false);}///  计算中心矩: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);}/// 绘制轮廓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);}/// 显示到窗口中namedWindow("Contours", CV_WINDOW_AUTOSIZE);imshow("Contours", drawing);/// 通过m00计算轮廓面积并且和OpenCV函数比较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 运行结果

实例1运行结果

实例2运行结果

实例3运行结果

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【OpenCV 】计算物体的凸包/创建包围轮廓的矩形和圆形边界框/createTrackbar添加滑动条/

topic 1:模板匹配

topic 2:图像中寻找轮廓

topic 3:计算物体的凸包

topic 4:轮廓创建可倾斜的边界框和椭圆¶

topic 5:轮廓矩¶

topic 6:为程序界面添加滑动条¶

3.1 目标

3.2 代码实例1

3.3 代码实例2

3.4 实例3运行结果

3.5 运行结果

【OpenCV 】计算物体的凸包/创建包围轮廓的矩形和圆形边界框/createTrackbar添加滑动条/相关推荐

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