Android OpenCV getPerspectiveTransform 和 warpPerspective

Question

我对 getPerspectiveTransform 的参数有点困惑，因为我看不到正确的图像。这是我的代码。 original_image 变量是包含我想要裁剪并创建新图像的方形对象（和其他一些对象）的图像（类似于Android OpenCV Find Largest Square or Rectangle）。变量 p1、p2、p3 和 p4 是图像中最大正方形/矩形角的坐标。 p1为左上，p2为右上，p3为右下，p4为左下（顺时针分配）。

    Mat src = new Mat(4,1,CvType.CV_32FC2);
    src.put((int)p1.y,(int)p1.x, (int)p2.y,(int)p2.x, (int)p4.y,(int)p4.x, (int)p3.y,(int)p3.x);
    Mat dst = new Mat(4,1,CvType.CV_32FC2);
    dst.put(0,0, 0,original_image.width(), original_image.height(),original_image.width(), original_image.height(),0);

    Mat perspectiveTransform = Imgproc.getPerspectiveTransform(src, dst);
    Mat cropped_image = original_image.clone();
    Imgproc.warpPerspective(untouched, cropped_image, perspectiveTransform, new Size(512,512));

当我尝试显示cropped_image 时，我得到一个“我不知道它是什么”的图像。我认为我在 getPerspectiveTransform() 中的参数不正确（或者是这样）。请帮忙。谢谢！

更新：当我调试我的代码时，我发现我的正方形/矩形的边缘不正确，除了 p4 之外，有些是完全正确的。这是我检测图像中正方形或矩形边缘的代码。除了具有白色轮廓的最大正方形/矩形的轮廓外，我的图像都是黑色的。

    //we will find the edges of the new_image (corners of the square/rectangle)
    Point p1 = new Point(10000, 10000); //upper left; minX && minY
    Point p2 = new Point(0, 10000); //upper right; maxX && minY
    Point p3 = new Point(0, 0); //lower right; maxX && maxY
    Point p4 = new Point(10000, 0); //lower left; minX && maxY
    double[] temp_pixel_color;
    for (int x=0; x<new_image.rows(); x++) {
        for (int y=0; y<new_image.cols(); y++) {
            temp_pixel_color = new_image.get(x, y); //we have a black and white image so we only have one color channel
            if (temp_pixel_color[0] > 200) { //we found a white pixel
                if (x<=p1.x && y<=p1.y) { //for p1, minX && minY
                    p1.x = x;
                    p1.y = y;
                }
                else if (x>=p2.x && y<=p2.y) { //for p2, maxX && minY
                    p2.x = x;
                    p2.y = y;
                }
                else if (x>=p3.x && y>=p3.y) { //for p3, maxX && maxY
                    p3.x = x;
                    p3.y = y;
                }
                else if (x<=(int)p4.x && y>=(int)p4.y) { //for p4, minX && maxY
                    p4.x = x;
                    p4.y = y;
                }
            }
        }
    }

这是我的示例图片。在检测到边缘后绘制彩色圆圈时忽略它们：

更新：2013 年 7 月 16 日 我现在可以仅使用最大 4 点轮廓的 approxCurve 来检测拐角。这是我的代码：

private Mat findLargestRectangle(Mat original_image) {
    Mat imgSource = original_image;
    //Mat untouched = original_image.clone();

    //convert the image to black and white
    Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);

    //convert the image to black and white does (8 bit)
    Imgproc.Canny(imgSource, imgSource, 50, 50);

    //apply gaussian blur to smoothen lines of dots
    Imgproc.GaussianBlur(imgSource, imgSource, new Size(5, 5), 5);      

    //find the contours
    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Imgproc.findContours(imgSource, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);

    double maxArea = -1;
    int maxAreaIdx = -1;
    MatOfPoint temp_contour = contours.get(0); //the largest is at the index 0 for starting point
    MatOfPoint2f approxCurve = new MatOfPoint2f();
    MatOfPoint2f maxCurve = new MatOfPoint2f();
    List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
    for (int idx = 0; idx < contours.size(); idx++) {
        temp_contour = contours.get(idx);
        double contourarea = Imgproc.contourArea(temp_contour);
        //compare this contour to the previous largest contour found
        if (contourarea > maxArea) {
            //check if this contour is a square
            MatOfPoint2f new_mat = new MatOfPoint2f( temp_contour.toArray() );
            int contourSize = (int)temp_contour.total();
            Imgproc.approxPolyDP(new_mat, approxCurve, contourSize*0.05, true);
            if (approxCurve.total() == 4) {
                maxCurve = approxCurve;
                maxArea = contourarea;
                maxAreaIdx = idx;
                largest_contours.add(temp_contour);
            }
        }
    }

    //create the new image here using the largest detected square
    Mat new_image = new Mat(imgSource.size(), CvType.CV_8U); //we will create a new black blank image with the largest contour
    Imgproc.cvtColor(new_image, new_image, Imgproc.COLOR_BayerBG2RGB);
    Imgproc.drawContours(new_image, contours, maxAreaIdx, new Scalar(255, 255, 255), 1); //will draw the largest square/rectangle

    double temp_double[] = maxCurve.get(0, 0);
    Point p1 = new Point(temp_double[0], temp_double[1]);
    Core.circle(new_image, new Point(p1.x, p1.y), 20, new Scalar(255, 0, 0), 5); //p1 is colored red
    String temp_string = "Point 1: (" + p1.x + ", " + p1.y + ")";

    temp_double = maxCurve.get(1, 0);
    Point p2 = new Point(temp_double[0], temp_double[1]);
    Core.circle(new_image, new Point(p2.x, p2.y), 20, new Scalar(0, 255, 0), 5); //p2 is colored green
    temp_string += "\nPoint 2: (" + p2.x + ", " + p2.y + ")";

    temp_double = maxCurve.get(2, 0);       
    Point p3 = new Point(temp_double[0], temp_double[1]);
    Core.circle(new_image, new Point(p3.x, p3.y), 20, new Scalar(0, 0, 255), 5); //p3 is colored blue
    temp_string += "\nPoint 3: (" + p3.x + ", " + p3.y + ")";

    temp_double = maxCurve.get(3, 0);
    Point p4 = new Point(temp_double[0], temp_double[1]);
    Core.circle(new_image, new Point(p4.x, p4.y), 20, new Scalar(0, 255, 255), 5); //p1 is colored violet
    temp_string += "\nPoint 4: (" + p4.x + ", " + p4.y + ")";

    TextView temp_text = (TextView)findViewById(R.id.temp_text);
    temp_text.setText(temp_string);

    return new_image;
}

这是示例结果图像：

我已经为正方形/矩形的角画了圆圈，我还添加了一个文本视图来显示所有四个点。

Answer 1

这对我有用。在 src_mat.put 中，首先应该有 0,0，然后是坐标的浮点值。

    Mat mat=Highgui.imread("inputImage.jpg");
    Mat src_mat=new Mat(4,1,CvType.CV_32FC2);
    Mat dst_mat=new Mat(4,1,CvType.CV_32FC2);


    src_mat.put(0,0,407.0,74.0,1606.0,74.0,420.0,2589.0,1698.0,2589.0);
    dst_mat.put(0,0,0.0,0.0,1600.0,0.0, 0.0,2500.0,1600.0,2500.0);
    Mat perspectiveTransform=Imgproc.getPerspectiveTransform(src_mat, dst_mat);

    Mat dst=mat.clone();

    Imgproc.warpPerspective(mat, dst, perspectiveTransform, new Size(1600,2500));
    Highgui.imwrite("resultImage.jpg", dst);