Question

目标：从相机的透视图中取一个点（或一组点）并将它们/它们转换为相应的地平面点。

方法：使用findHomography获取单应性Mat。计划使用perspectiveTransform()。

问题：无法解读单应性Mat，也无法理解如何继续。它看起来9个元素中有5个是空的，我认为这是因为单应性是错误的，虽然无法解释结果，所以制作了许多印刷语句。

import org.opencv.calib3d.*;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.*;

import java.util.List;
import java.util.LinkedList;
import java.util.ArrayList;

final public class HomographyTest {

    public static void main(String[] args) {

        System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // needed by OpenCV

        String rfileoutput = "/home/will/dev/Homog.jpg";
        String ofileoutput = "/home/will/dev/HomogOutput.jpg";

        Point SEShedCornerDst = new Point(49, 74);
        Point CloseForsythiaDst = new Point(41, 41);
        Point CornerHazelDst = new Point(111, 157);
        Point FarForsythiaDst = new Point(175, 21);
        Point FirstLiquidAmberDst = new Point(235, 164);
        Point SecondLiquidAmberDst = new Point(282, 721);
        Point ThirdLiquidAmberDst = new Point(317, 544);

        Point SEShedCornerSrc = new Point(30, 231);
        Point CloseForsythiaSrc = new Point(160, 290);
        Point CornerHazelSrc = new Point(50, 125);
        Point FarForsythiaSrc = new Point(628, 146);
        Point FirstLiquidAmberSrc = new Point(299, 64);
        Point SecondLiquidAmberSrc = new Point(146, 37);
        Point ThirdLiquidAmberSrc = new Point(48,34);

        Point [] srcArray = new Point[7];
        srcArray[0] = SEShedCornerSrc;
        srcArray[1] = CloseForsythiaSrc;
        srcArray[2] = CornerHazelSrc;
        srcArray[3] = FarForsythiaSrc;
        srcArray[4] = FirstLiquidAmberSrc;
        srcArray[5] = SecondLiquidAmberSrc;
        srcArray[6] = ThirdLiquidAmberSrc;

        Mat OutputMat = new Mat();
        LinkedList<Point> dstArray = new LinkedList<Point>();

        dstArray.add(SEShedCornerDst);
        dstArray.add(CloseForsythiaDst);        
        dstArray.add(CornerHazelDst);
        dstArray.add(FarForsythiaDst);
        dstArray.add(FirstLiquidAmberDst);
        dstArray.add(SecondLiquidAmberDst);
        dstArray.add(ThirdLiquidAmberDst);

        MatOfPoint2f dst = new MatOfPoint2f();
        dst.fromList(dstArray);

        MatOfPoint2f src = new MatOfPoint2f();
        src.fromArray(srcArray);

        Mat Homog;


        Homog = Calib3d.findHomography(src, dst, Calib3d.RANSAC, 10, OutputMat);

        System.out.println("Columns = " + Homog.cols());
        System.out.println("Rows = " + Homog.rows());
        System.out.println("Width = " + Homog.width());
        System.out.println("Dims = " + Homog.dims());

        for (int i=1; i<= Homog.cols();i++){
            for (int j=1; j<=Homog.rows();j++){
                System.out.println("Row, column " + i + "," + j + " = " + Homog.get(j, i));
            }
            System.out.println();
        }
        System.out.println(Homog.toString());
        System.out.println(OutputMat.toString());
        Highgui.imwrite(rfileoutput, Homog);
        Highgui.imwrite(ofileoutput, OutputMat);
    }
}

输出;

Columns = 3
Rows = 3
Width = 3
Dims = 2
Row, column 1,1 = [D@674f1c67
Row, column 1,2 = [D@7ad1e32d
Row, column 1,3 = null

Row, column 2,1 = [D@6999de59
Row, column 2,2 = [D@74d4db38
Row, column 2,3 = null

Row, column 3,1 = null
Row, column 3,2 = null
Row, column 3,3 = null

Mat [ 3*3*CV_64FC1, isCont=true, isSubmat=false, nativeObj=0x7f744016bb50, dataAddr=0x7f744016b940 ]
Mat [ 7*1*CV_8UC1, isCont=true, isSubmat=false, nativeObj=0x7f7440166fe0, dataAddr=0x7f744016b9b0 ]

我是否在正确的轨道上？如果没有，我该怎么办？

如果是，请在Mat的src perspectiveTransform中输入什么类型，如何在需要的两个频道中执行此操作？

http://docs.opencv.org/java/org/opencv/core/Core.html#perspectiveTransform(org.opencv.core.Mat,%20org.opencv.core.Mat,%20org.opencv.core.Mat)

Answer 1

我无法真正解释你的代码，特别是你的观点，但我认为这并不重要，因为正如你所说的那样，你的目标是从2组点创建单应矩阵，并用生成的单应矩阵透视变换图像

迭代单应矩阵

首先，你通过单应矩阵（3x3矩阵）从迭代中得到null的原因是因为Mat索引就像0处的数组一样开始，结束于“长度 - 1" 。

看起来应该是这样的：

for (int i = 0; i < homography.cols(); i++){
    for (int j = 0; j < homography.rows(); j++){
        System.out.println("[" + i + "," + j + "] = " + Arrays.toString(homography.get(j, i)));
    }
}

查找单应性并应用（到图像）

要查找src和dst平面之间的单应矩阵，您可以使用findHomography()。有关此函数的更多信息，请参阅API

中的参数

// obtain your homography mat (picked your parameters.. you have to play to get the right results)
Mat homography = Calib3d.findHomography(src, dst, Calib3d.RANSAC, 10);
// image you want to transform
Mat image = Highgui.imread("image/img.jpg");
// outputMat will contain the perspectively changed image
Imgproc.warpPerspective(image, outputMat, homography, new Size(image.cols(), image.rows()));

将单应性应用于单点（非图像）

Mat src = new Mat();
// push a mat object with your points to the src
src.push_back(new MatOfPoint2f(new Point(x,y)));
// dst will contain your transformed points
Core.perspectiveTransform(src, dst, homography)

Btw ..

在Java中，通常的做法是使用小写字母启动变量名称。我看到了Homog和OutputMat。当我读到类似的东西时，我希望它们是课程。

Java findHomography变换图像指向地平面点

1 个答案: