一简介
1、凸包
凸包(Convex Hull)是一个计算机几何图形学中的概念, 简单来说, 给定二维平面点集, 凸包就是能够将最外层的点连接起来构成的凸多边形, 它能够包含点集中所有的点。物体的凸包检测场应用在物体识别、手势识别及边界检测等领域。
A-H是被标出的凸包缺陷
2、寻找凸包---convexHull()
1 CV_EXPORTS_W void convexHull(InputArray points, OutputArray hull, bool clockwise=false, bool returnPoints = true);
points: 输入的二维点集, 可以填Mat类型或std::vector
hull: 函数调用后找到的凸包
clockwise: 操作方向标志符, 当为true时, 输出的凸包为顺时针方向, false为逆时针方向(假定坐标系x轴指向右，y轴指向上方)
returnPoints: 操作标志符, 默认值true. 当标志符为true时, 函数返回凸包各个点, 否则返回凸包各点的指数, 当输出数组是std::vector时, 此标志被忽略
示例：
1 vector<int> hull;
2 convexHull(Mat(points), hull, true);
1 vector<vector<Point>> hull(contours.size());
2 for(int i = 0; i < contours.size(); i++)
3 {
4 convexHull(Mat(contours[i]), hull[i], true);
5 }
3、凸包缺陷分析---convexityDefects()
1 CV_EXPORTS_W void convexityDefects(InputArray contour, InputArray convexhull, OutputArray convexityDefects);
contour: 表示输入参数检测到的轮廓, 可以用findContours函数获得
convexhull: 输入参数表示检测到的凸包, 可以用convexHull函数获得
convexityDefects: 检测到的最终结果, 应为vector<vector
二、绘制点集的凸包
1 //绘制点集的凸包
2 #include<opencv2/opencv.hpp>
3
4 using namespace cv;
5
6 int main()
7 {
8 //---绘制点集的凸包
9 Mat img(400, 400, CV_8UC3, Scalar::all(0)); //定义绘制图像
10 RNG rng; //定义随机数对象
11 while(1)
12 {
13 char key;
14 int count = (unsigned int)rng % 100; //定义点的个数
15 vector<Point> points; //定义点集
16 for(int i=0; i<count; i++)
17 {
18 Point pt;
19 pt.x = rng.uniform(img.cols/4, img.cols*3/4); //设定点的x范围
20 pt.y = rng.uniform(img.rows/4, img.rows*3/4); //设定点的y范围
21 points.push_back(pt);
22 }
23
24 //检测凸包
25 vector<int> hull;
26 convexHull(Mat(points), hull, true);
27
28 img = Scalar::all(0);
29 for(int i = 0; i < count; i++ )
30 circle(img, points[i], 3, Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), CV_FILLED, CV_AA);
31
32 //准备参数
33 int hullcount = (int)hull.size(); //凸包的边数
34 Point point0 = points[hull[hullcount-1]]; //连接凸包边的坐标点
35
36 //绘制凸包的边
37 for(int i = 0; i < hullcount; i++ )
38 {
39 Point point = points[hull[i]];
40 circle(img, point, 8, Scalar(0, 255, 0), 2, 8);
41 line(img, point0, point, Scalar(255, 255, 255), 2, CV_AA);
42 point0 = point;
43 }
44
45 //显示效果图
46 imshow("img", img);
47
48 //按下ESC,Q,或者q，程序退出
49 key = (char)waitKey();
50 if( key == 27 || key == 'q' || key == 'Q' )
51 break;
52 }
53 return 0;
54 }
三、绘制轮廓的凸包
1 //绘制轮廓的凸包
2 #include<opencv2/opencv.hpp>
3
4 using namespace cv;
5
6 int main()
7 {
8 Mat srcImg = imread("12.jpg");
9 imshow("src", srcImg);
10 Mat dstImg2 = srcImg.clone();
11 Mat tempImg(srcImg.rows, srcImg.cols, CV_8UC3, Scalar::all(0)); //用于绘制凸包
12 Mat dstImg(srcImg.rows, srcImg.cols, CV_8UC3, Scalar::all(0)); //用于绘制轮廓
13 cvtColor(srcImg, srcImg, CV_BGR2GRAY);
14 threshold(srcImg, srcImg, 100, 255, CV_THRESH_BINARY); //二值化
15
16 vector<vector<Point>> contours;
17 vector<Vec4i> hierarcy;
18 findContours(srcImg, contours, hierarcy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
19 vector<vector<Point>> hull(contours.size());
20 for(int i=0; i<contours.size(); i++)
21 {
22 convexHull(Mat(contours[i]), hull[i], true); //查找凸包
23 drawContours(dstImg, contours, i, Scalar(255, 255, 255), -1, 8); //绘制轮廓
24 //drawContours(dstImg, hull, i, Scalar(rand()%255, rand()%255, rand()%255), 2, 8);
25 drawContours(tempImg, hull, i, Scalar(255, 255, 255), -1, 8);
26 }
27 imshow("hull", tempImg);
28 imshow("contours", dstImg);
29
30 Mat diffImg;
31 absdiff(tempImg, dstImg, diffImg); //图像相减
32 Mat element = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
33 erode(diffImg, diffImg, element);
34 imshow("diff", diffImg);
35
36 vector<vector<Point>> contours2;
37 vector<Vec4i> hierarcy2;
38 cvtColor(diffImg, diffImg, CV_BGR2GRAY); //转为灰度图
39 threshold(diffImg, diffImg, 100, 255, CV_THRESH_BINARY); //二值化
40 findContours(diffImg, contours2, hierarcy2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
41 drawContours(dstImg2, contours2, -1, Scalar(0, 0, 255), 2, 8); //红色绘制缺陷轮廓
42 imshow("defects", dstImg2);
43 waitKey(0);
44 return 0;
45 }
