opencv3計算影象中輪廓的面積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);  
    //轉換為二值圖    
    Mat binaryImage;  
    threshold(grayImage, binaryImage, 90, 255, CV_THRESH_BINARY);  

    //二值圖 這裡進行了畫素反轉，因為一般我們用255白色表示前景（物體），用0黑色表示背景    
 

    Mat reverseBinaryImage;  
    bitwise_not(binaryImage, reverseBinaryImage);  

    vector <vector<Point>>contours;  
    findContours(reverseBinaryImage,  
        contours,   //輪廓的陣列  
        CV_RETR_EXTERNAL,   //獲取外輪廓  
        CV_CHAIN_APPROX_NONE);  //獲取每個輪廓的每個畫素  
    //在白色影象上繪製黑色輪廓  
 

    Mat result(reverseBinaryImage.size(), CV_8U, Scalar(255));  
    drawContours(result, contours,  
        -1, //繪製所有輪廓  
        Scalar(0),  //顏色為黑色  
        2); //輪廓線的繪製寬度為2  

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

    //移除過長或過短的輪廓  
    int cmin = 100; //最小輪廓長度  
    int cmax = 1000;    //最大輪廓  
    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;  
    }  

    //在白色影象上繪製黑色輪廓  
    Mat result_erase(binaryImage.size(), CV_8U, Scalar(255));  
    drawContours(result_erase, contours,  
        -1, //繪製所有輪廓  
        Scalar(0),  //顏色為黑色  
        2); //輪廓線的繪製寬度為2  

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