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¶
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