精确寻找一个圆（接的一个小外包）

  1 #include<iostream>
  2 #include <opencv2/opencv.hpp>
  3 #include <math.h>
  4 using namespace cv;
  5 using namespace std;
  6 
  7 int Threshold_Value = 176;
  8 const int Threshold_Max_value = 255;
  9 const int Threshold_type_value = 3;
 10 
 11 Mat input_image, threshold_image, output_image, Middle_image;
 12 
 13 void Threshold_Image_Bar(int, void *);
 14 
 15 int main(int argc, char**argv)
 16 {
 17     input_image = imread("b.jpg");
 18     if (input_image.data == NULL) {
 19         return -1; cout << "can‘t open image.../";
 20     }
 21     //----------简单预处理
 22     imshow("Sourse Image", input_image);
 23     blur(input_image, Middle_image, Size(3, 3), Point(-1, -1), 4);
 24     imshow("Blur Image", Middle_image);
 25     cvtColor(Middle_image, Middle_image, COLOR_RGB2GRAY);
 26     imshow("Gray Image", Middle_image);
 27     //-----------利用比例对图像进行ROI操作
 28     const float init_pointx =  saturate_cast<float>(Middle_image.cols / 7);
 29     const float init_pointy =  saturate_cast<float>(Middle_image.rows / 7);
 30     Rect roi_rect = Rect(Point2f(2 * init_pointx, 2 * init_pointy), Point2f(6 * init_pointx, 6 * init_pointy));
 31     Mat  roi_Image = Middle_image(roi_rect);
 32     Middle_image = roi_Image;
 33     //----------这里使用大法定律自适应操作图像，程序的稳定性很高
 34     threshold(Middle_image, threshold_image, 0, 255, THRESH_BINARY_INV | THRESH_OTSU);//这个65可以更改看效果
 35     imshow("Threshold Image", threshold_image);
 36     //----------这里通过形态学操作对图像稍作调整
 37     Mat kernel_rect   = getStructuringElement(MORPH_ELLIPSE, Size(30, 30), Point(-1, -1));
 38     Mat kernel_circle = getStructuringElement(MORPH_ELLIPSE, Size(10, 10), Point(-1, -1));
 39     morphologyEx(threshold_image, threshold_image, MORPH_CLOSE, kernel_circle);
 40     Mat RedImage = threshold_image.clone();
 41     /*--------这是当时求外面圆的代码，这里不需要了，求外面的圆不准确
 42     Mat otherImage;
 43     Canny(threshold_image, otherImage, 50, 200);
 44     vector<vector<Point>> contours;
 45     vector<Vec4i> hierarchy;
 46     Mat showImage = Mat::zeros(RedImage.size(), CV_8UC1);
 47     findContours(RedImage, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(-1, -1));
 48     for (size_t i = 0; i < contours.size(); i++)
 49     {
 50     if (boundingRect(contours[i]).area() > 10000)//这个参数大概就可以
 51     {
 52     drawContours(showImage, contours, static_cast<int>(i), Scalar(255, 255, 255), 1);
 53     Point2f center;
 54     float radius;
 55     minEnclosingCircle(contours[i], center, radius);
 56     Mat result = Mat::zeros(RedImage.size(), CV_8UC3);
 57     circle(input_image, center, radius, Scalar(0, 0, 255), 2);
 58     }
 59     }
 60     */
 61     morphologyEx(RedImage, threshold_image, MORPH_OPEN, kernel_rect);
 62     //---------图像删除旁边干扰区域
 63     for (size_t i = 0; i < threshold_image.rows; i++)
 64     {
 65         for (size_t j = 0; j < threshold_image.cols; j++)
 66         {
 67             RedImage.at<uchar>(i, j) = saturate_cast<uchar>(RedImage.at<uchar>(i, j) - threshold_image.at<uchar>(i, j));
 68         }
 69     }
 70     vector<vector<Point>> contours;
 71     vector<Vec4i> hierarchy;
 72     Mat showImage = Mat::zeros(RedImage.size(), CV_8UC1);
 73     findContours(RedImage, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(-1, -1));
 74     for (size_t i = 0; i < contours.size(); i++)
 75     {
 76         //------如果圆找的位置太离谱，这里可进行优化
 77         //------如果找的圆位置不精确这里更改数字
 78         if (minAreaRect(contours[i]).size.area() > 10000 && minAreaRect(contours[i]).size.height > 80 && minAreaRect(contours[i]).size.width > 80)//这个参数大概就可以
 79         {
 80             drawContours(showImage, contours, static_cast<int>(i), Scalar(255, 255, 255), 1);
 81         }
 82     }
 83     //-----------将点存入容器进行点集操作
 84     vector<Point> points;
 85     for (int i = 0; i < showImage.rows; i++)
 86     {
 87         for (int j = 0; j < showImage.cols; j++)
 88         {
 89             if (showImage.at<uchar>(i, j) == 255)
 90             {
 91                 points.push_back(Point(j, i));
 92             }
 93         }
 94     }
 95     //----------点拟合圆，这里代码只是找一个圆，也可优化成找多个圆
 96     Point2f center;
 97     float radius;
 98     if (points.data() == 0)
 99     {
100         printf("Don‘t detecte point");
101         return -1;
102     }
103     minEnclosingCircle(points, center, radius);
104     center.x += 2 * init_pointx;
105     center.y += 2 * init_pointy;
106     Mat result = Mat::zeros(RedImage.size(), CV_8UC3);
107     circle(input_image, center, radius, Scalar(0, 0, 255), 2);
108 
109     /*namedWindow("Threshold Image", 1);
110     createTrackbar("阈值调整", "Threshold Image", &Threshold_Value, 255, Threshold_Image_Bar);
111     Threshold_Image_Bar(0, 0);*/
112     imshow("result", input_image);
113     waitKey(0);
114     return 0;
115 }
116 //------这是调试用的滑块，已经调试好了，代码搬上去了，如果你需要调试那就再使用
117 void Threshold_Image_Bar(int, void *)
118 {
119     threshold(Middle_image, threshold_image, 65, 255,THRESH_BINARY_INV);//110,65
120     imshow("Threshold Image", threshold_image);
121     Mat kernel = getStructuringElement(MORPH_RECT, Size(50, 50), Point(-1, -1));//这个参数无所谓的
122     Mat RedImage = threshold_image.clone();
123     /*
124     Mat otherImage;
125     Canny(threshold_image, otherImage, 50, 200);
126     vector<vector<Point>> contours;
127     vector<Vec4i> hierarchy;
128     Mat showImage = Mat::zeros(RedImage.size(), CV_8UC1);
129     findContours(RedImage, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(-1, -1));
130     for (size_t i = 0; i < contours.size(); i++)
131     {
132         if (boundingRect(contours[i]).area() > 10000)//这个参数大概就可以
133         {
134             drawContours(showImage, contours, static_cast<int>(i), Scalar(255, 255, 255), 1);
135             Point2f center;
136             float radius;
137             minEnclosingCircle(contours[i], center, radius);
138             Mat result = Mat::zeros(RedImage.size(), CV_8UC3);
139             circle(input_image, center, radius, Scalar(0, 0, 255), 2);
140         }
141     }
142     */
143     morphologyEx(RedImage, threshold_image, MORPH_OPEN, kernel);
144     for (size_t i = 0; i < threshold_image.rows; i++)
145     {
146         for (size_t j = 0; j < threshold_image.cols; j++)
147         {
148             RedImage.at<uchar>(i, j) = saturate_cast<uchar>(RedImage.at<uchar>(i, j) - threshold_image.at<uchar>(i, j));
149         }
150     }
151     vector<vector<Point>> contours;
152     vector<Vec4i> hierarchy;
153     Mat showImage = Mat::zeros(RedImage.size(), CV_8UC1);
154     findContours(RedImage, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(-1, -1));
155     for (size_t i = 0; i < contours.size(); i++)
156     {
157         if (boundingRect(contours[i]).area() > 20000)//这个参数大概就可以
158         {
159             drawContours(showImage, contours, static_cast<int>(i), Scalar(255, 255, 255), 1);
160         }
161     }
162     vector<Point> points;
163     for (int i = 0; i < showImage.rows; i++)
164     {
165         for (int j = 0; j < showImage.cols; j++)
166         {
167             if (showImage.at<uchar>(i, j) == 255)
168             {
169                 points.push_back(Point(j, i));
170             }
171         }
172     }
173     Point2f center;
174     float radius;
175     minEnclosingCircle(points, center, radius);
176     Mat result = Mat::zeros(RedImage.size(), CV_8UC3);
177     circle(input_image, center, radius, Scalar(0, 0, 255), 2);
178 }