opencv學習之路（39）、PCA

1、PCA理論介紹

網上已經有許多介紹pca原理的博客，這裏就不重複介紹了。詳情可參考

http://blog.csdn.net/zhongkelee/article/details/44064401

計算過程

數據互換

2、opencv代碼

#include<opencv2/opencv.hpp>
using namespace cv;
using namespace std;

void calcPCAOrientation(vector<Point>&pts, Mat &image){
    int size = static_cast<int>(pts.size());//static_cast強制類型轉換
    Mat data_pts = Mat(size,2,CV_64FC1);//size個對象，2個維度(即平面座標x，y)
    for (int i = 0; i < size; i++)
    {
        data_pts.at<double>(i, 0) = pts[i].x;
        data_pts.at<double>(i, 1) = pts[i].y;
    }
    //執行PCA的一系列步驟：樣本數據-均值，算協方差，算特徵值和特徵向量……
    PCA pca(data_pts, Mat(), CV_PCA_DATA_AS_ROW);
    //獲取均值（中心）位置
    Point cnt = Point(static_cast<int>(pca.mean.at<double>(0, 0)),
                      static_cast<int>(pca.mean.at<double>(0, 1)));
    circle(image,cnt,2,Scalar(0,255,0),2,8,0);

    vector<Point2d>vecs(2);
    vector<double>vals(2);
    for (int i = 0; i < 2; i++)
    {
        vals[i] = pca.eigenvalues.at<double>(i, 0);//特徵值
        cout << "第" << i << "個特徵值：" << vals[i]<<endl;
        vecs[i] = Point2d(pca.eigenvectors.at<double>(i, 0),    //特徵向量
                         (pca.eigenvectors.at<double>(i, 1)));
    }
    Point p1 = cnt + 0.02*Point(static_cast<int>(vecs[0].x*vals[0]), static_cast<int>(vecs[0].y*vals[0]));
    Point p2  = cnt - 0.05*Point(static_cast<int>(vecs[1].x*vals[1]), static_cast<int>(vecs[1].y*vals[1]));

    line(image, cnt, p1, Scalar(255, 0, 0), 2, 8, 0);
    line(image, cnt, p2, Scalar(255, 255, 0), 2, 8, 0);

    double angle = atan2(vecs[0].y,vecs[0].x);
    cout << "angle:" << 180 * (angle / CV_PI)<<endl;
}

void main()
{
    Mat src = imread("E://2.jpg");
    imshow("src", src);
    Mat gray, binary;
    cvtColor(src, gray,CV_BGR2GRAY);
    threshold(gray, binary,0,255, THRESH_BINARY|THRESH_OTSU);//自動閾值：OTSU找到一個它認爲最好的閾值
    //imshow("binary", binary);

    //輪廓提取
    vector<Vec4i>hierarchy;
    vector<vector<Point>>contours;
    findContours(binary, contours, hierarchy, RETR_LIST, CHAIN_APPROX_NONE);//查找全部輪廓，存儲全部輪廓點
    Mat result = src.clone();//複製，不隨原圖改變
    for (int i = 0; i < contours.size(); i++)
    {
        double area = contourArea(contours[i]);
        if (area>1e5 || area < 1e2)    continue;//面積大於10^5或者小於10^2的輪廓，不要
        drawContours(result, contours, i, Scalar(0, 0, 255), 2, 8);

        calcPCAOrientation(contours[i], result);//調用PCA
    }
    imshow("contours result", result);

    waitKey(0);
}