计算物体的凸包

        凸包跟多边形逼近很像，只不过它是物体最外层的"凸"多边形：集合A内连接任意两个点的直线都在A的内部，则称集合A是凸形的。如下图，红色的部分为手掌的凸包，双箭头部分表示凸缺陷(Convexity Defects)，凸缺陷常用来进行手势识别等；

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
//设置全局参数
Mat srcImage, srcGray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);
void thresh_callback(int, void*)
{
    Mat srcTemp = srcImage.clone();
    Mat threMat;
    //轮廓检测参数
    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;
    //阈值化操作
    threshold(srcGray, threMat, thresh, 255, THRESH_BINARY);
    //轮廓检测
    findContours(threMat, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
    //凸包及缺陷检测参数
    vector<vector<Point> > pointHull(contours.size());
    vector<vector<int> > intHull(contours.size());
    vector<vector<Vec4i> > hullDefect(contours.size());
    for (size_t i = 0; i < contours.size(); i++)
    {
        //Point类型凸包检测
        convexHull(Mat(contours[i]), pointHull[i], false);
        //int 类型凸包检测
        convexHull(Mat(contours[i]), intHull[i], false);
        //凸包缺陷检测
        convexityDefects(Mat(contours[i]), intHull[i], hullDefect[i]);
    }
    //绘制凸包及缺陷检测
    Mat drawing = Mat::zeros(threMat.size(), CV_8UC3);
    for (size_t 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, pointHull, i, color, 1, 8, vector<Vec4i>(), 0, Point());
        //绘制缺陷
        size_t count = contours[i].size();
        if (count < 300)
            continue;
        //设置凸包缺陷迭代器
        vector<Vec4i>::iterator iterDefects = hullDefect[i].begin();
        //遍历得到4个特征量
        while (iterDefects != hullDefect[i].end())
        {
            Vec4i& v = (*iterDefects);
            //起始位置
            int startidx = v[0];
            Point ptStart(contours[i][startidx]);
            //终止位置
            int endidx = v[1];
            Point ptEnd(contours[i][endidx]);
            //内凸壳最远的点缺陷
            int faridx = v[2];
            Point ptFar(contours[i][faridx]);
            //凸点之间的最远点
            int depth = v[3] / 256;
            //绘制相应的线与圆检测结果
            if (depth > 20 && depth < 80)
            {
                line(drawing, ptStart, ptFar, CV_RGB(0, 255, 0), 2);
                line(drawing, ptEnd, ptFar, CV_RGB(0, 255, 0), 2);
                circle(drawing, ptStart, 4, Scalar(255, 0, 100), 2);
                circle(drawing, ptEnd, 4, Scalar(255, 0, 100), 2);
                circle(drawing, ptFar, 4, Scalar(100, 0, 255), 2);
            }
            iterDefects++;
        }
    }
    imshow("result", drawing);
}
int main()
{
    srcImage = imread("E:\\VS2015Opencv\\vs2015\\project\\picture\\01.jpg");
    if (!srcImage.data)
        return -1;
    cvtColor(srcImage, srcGray, CV_BGR2GRAY);
    blur(srcGray, srcGray, Size(3, 3));

    char* sour_window = "Sourse";
    namedWindow(sour_window, CV_WINDOW_AUTOSIZE);
    imshow(sour_window, srcImage);
    createTrackbar("Thewshold:", sour_window, &thresh, max_thresh, thresh_callback);
    thresh_callback(0, 0);
    waitKey(0);
    return 0;
}