opencv——對象計數

標籤：nsf   info   opencv   篩選   pre   ios   pen   extern   tco   

 思路：

1、通過形態學操作、閾值處理、距離變換等方法，使得各個輪廓分開

2、計算輪廓數量

 

 1 #include <opencv2/opencv.hpp> 2 #include <iostream> 3 #include <math.h> 4  5 using namespace cv; 6 using namespace std; 7  8  9 int main(int argc, char** argv)10 {11     Mat src = imread("計數.jpg");12     //medianBlur(src, src,5);//中值濾波，去除椒鹽雜訊13     imshow("src", src);14 15     Mat src_gray,binary;16     17     cvtColor(src,src_gray,COLOR_BGR2GRAY);18     19     threshold(src_gray,binary,0,255,THRESH_BINARY|THRESH_TRIANGLE);//顏色單一時，使用THRESH_TRIANGLE比OTSU好20     imshow("binary", binary);21 22     //形態學操作23     Mat kernel = getStructuringElement(MORPH_RECT,Size(5,5));24     dilate(binary, binary, kernel,Point(-1,-1),4);25 26     //距離變換27     Mat dist;28     bitwise_not(binary, binary);//取反29     distanceTransform(binary,dist,CV_DIST_L2,3);30     normalize(dist, dist,0,1.0,NORM_MINMAX);31     imshow("dist", dist);32 33     //閾值化二值分割34     //threshold(dist, dist,0.7,1.0,THRESH_BINARY);//對距離進行篩選，去除邊緣部分35     //normalize(dist, dist, 0, 255, NORM_MINMAX);36     Mat dist_8U;37     dist.convertTo(dist_8U,CV_8U);38     adaptiveThreshold(dist_8U, dist_8U, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 85, 0.0);//自適應閾值，代替上面的閾值操作39     //形態學操作，使得斷開部分串連40     kernel = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1));41     dilate(dist_8U, dist_8U, kernel, Point(-1, -1),3);42 43     imshow("dist_8U", dist_8U);44 45     // 連通地區計數46     vector<vector<Point>> contours;47     findContours(dist_8U, contours, CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);48 49     // draw result50     Mat markers = Mat::zeros(src.size(), CV_8UC3);51     RNG rng(12345);52     for (size_t t = 0; t < contours.size(); t++) {53         drawContours(markers, contours, static_cast<int>(t), Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)),54             -1, 8, Mat());55     }56     printf("number of corns : %d", contours.size());57     imshow("Final result", markers);58 59     waitKey(0);60 61     return 0;62 }

 

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace cv;
using namespace std;


int main(int argc, char** argv)
{
    Mat src = imread("計數.jpg");
    //medianBlur(src, src,5);//中值濾波，去除椒鹽雜訊
    imshow("src", src);

    Mat src_gray,binary;
    
    cvtColor(src,src_gray,COLOR_BGR2GRAY);
    
    threshold(src_gray,binary,0,255,THRESH_BINARY|THRESH_TRIANGLE);//顏色單一時，使用THRESH_TRIANGLE比OTSU好
    imshow("binary", binary);

    //形態學操作
    Mat kernel = getStructuringElement(MORPH_RECT,Size(5,5));
    dilate(binary, binary, kernel,Point(-1,-1),4);

    //距離變換
    Mat dist;
    bitwise_not(binary, binary);//取反
    distanceTransform(binary,dist,CV_DIST_L2,3);
    normalize(dist, dist,0,1.0,NORM_MINMAX);
    imshow("dist", dist);

    //閾值化二值分割
    //threshold(dist, dist,0.7,1.0,THRESH_BINARY);//對距離進行篩選，去除邊緣部分
    //normalize(dist, dist, 0, 255, NORM_MINMAX);
    Mat dist_8U;
    dist.convertTo(dist_8U,CV_8U);
    adaptiveThreshold(dist_8U, dist_8U, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 85, 0.0);//自適應閾值，代替上面的閾值操作
    //形態學操作，使得斷開部分串連
    kernel = getStructuringElement(MORPH_RECT, Size(5, 5), Point(-1, -1));
    dilate(dist_8U, dist_8U, kernel, Point(-1, -1),3);

    imshow("dist_8U", dist_8U);

    // 連通地區計數
    vector<vector<Point>> contours;
    findContours(dist_8U, contours, CV_RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);

    // draw result
    Mat markers = Mat::zeros(src.size(), CV_8UC3);
    RNG rng(12345);
    for (size_t t = 0; t < contours.size(); t++) {
        drawContours(markers, contours, static_cast<int>(t), Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)),
            -1, 8, Mat());
    }
    printf("number of corns : %d", contours.size());
    imshow("Final result", markers);

    waitKey(0);

    return 0;
}

opencv——對象計數