获取最大轮廓 opencv

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opencv3计算图像中轮廓的面积http://blog.csdn.net/qq_23880193/article/details/49256999

http://blog.csdn.net/davebobo/article/details/52583167

#include<iostream>    
#include <opencv2/core/core.hpp>      
#include <opencv2/highgui/highgui.hpp>   
#include<imgproc/imgproc.hpp>    

using namespace std;  
using namespace cv;  

int main(){  

    Mat image = cvLoadImage("group.jpg");  
    Mat grayImage;  
    cvtColor(image, grayImage, CV_BGR2GRAY);  
    //转换为二值图    
    Mat binaryImage;  
    threshold(grayImage, binaryImage, 90, 255, CV_THRESH_BINARY);  

    //二值图 这里进行了像素反转，因为一般我们用255白色表示前景（物体），用0黑色表示背景    
    Mat reverseBinaryImage;  
    bitwise_not(binaryImage, reverseBinaryImage);  

    vector <vector<Point>>contours;  
    findContours(reverseBinaryImage,  
        contours,   //轮廓的数组  
        CV_RETR_EXTERNAL,   //获取外轮廓  
        CV_CHAIN_APPROX_NONE);  //获取每个轮廓的每个像素  
    //在白色图像上绘制黑色轮廓  
    Mat result(reverseBinaryImage.size(), CV_8U, Scalar(255));  
    drawContours(result, contours,  
        -1, //绘制所有轮廓  
        Scalar(0),  //颜色为黑色  
        2); //轮廓线的绘制宽度为2  

    namedWindow("contours");  
    imshow("contours", result);  

    //移除过长或过短的轮廓  
    int cmin = 100; //最小轮廓长度  
    int cmax = 1000;    //最大轮廓  
    vector<vector<Point>>::const_iterator itc = contours.begin();  
    while (itc!=contours.end())  
    {  
        if (itc->size() < cmin || itc->size() > cmax)  
            itc = contours.erase(itc);  
        else  
            ++itc;  
    }  

    //在白色图像上绘制黑色轮廓  
    Mat result_erase(binaryImage.size(), CV_8U, Scalar(255));  
    drawContours(result_erase, contours,  
        -1, //绘制所有轮廓  
        Scalar(0),  //颜色为黑色  
        2); //轮廓线的绘制宽度为2  

    namedWindow("contours_erase");  
    imshow("contours_erase", result_erase);  
    waitKey(0);  
    return 0;  
}