使用Emgu检测显示角 [英] Detect display corners with Emgu

问题描述

我想检测图像上的显示(更确切地说是其角落).我将图片分割成显示颜色而不显示颜色:

I want to detect a display on an image (more precisely its corners). I segment the image in display color and not display color:

Image<Gray, byte> segmentedImage = greyImage.InRange(new Gray(180), new Gray(255));

然后我使用哈里斯角找到拐角:

Then I use corner Harris to find the corners:

Emgu.CV.Image<Emgu.CV.Structure.Gray, Byte> harrisImage = new Image<Emgu.CV.Structure.Gray, Byte>(greyImage.Size);
CvInvoke.CornerHarris(segmentedImage, harrisImage, 2);
CvInvoke.Normalize(harrisImage, harrisImage, 0, 255, NormType.MinMax, DepthType.Cv32F);

现在角落有白色像素，但我无法访问它们:

There are now white pixels in the corners, but I cannot access them:

for (int j = 0; j < harrisImage.Rows; j++)
{
    for (int i = 0; i < harrisImage.Cols; i++)
    {
        Console.WriteLine(harrisImage[j, i].Intensity);
    }
}

它只写0.如何访问它们?如果可以访问它们，如何在harris图像中找到屏幕的四个角?是否有一个功能可以从点中找到透视变换的矩形?

It writes only 0s. How can I access them? And if I can access them, how can I find the 4 corners of the screen in the harris image? Is there a function to find a perspectively transformed rectangle from points?

在OpenCV IRC上，他们说FindContours不够精确.当我尝试在segmentedImage上运行它时，我得到了:(在segmentedImage上运行FindContours，然后在ApproxPolyDP上运行，并在原始灰度图像上绘制找到的轮廓).
我无法找到更精确的轮廓...

On the OpenCV IRC they said FindContours is not that precise. And when I try to run it on the segmentedImage, I get this: (ran FindContours on the segmentedImage, then ApproxPolyDP and drew the found contour on the original greyscale image)
I cannot get it to find the contours more precise...

我无法让它为我工作.即使使用您的代码，我也会得到完全相同的结果...这是我的完整Emgu代码:

I cannot get this to work for me. Even with your code, I get the exact same result... Here is my full Emgu code:

Emgu.CV.Image<Emgu.CV.Structure.Gray, Byte> imageFrameGrey = new Image<Emgu.CV.Structure.Gray, Byte>(bitmap);
Image<Gray, byte> segmentedImage = imageFrameGrey.InRange(new Gray(180), new Gray(255));
// get rid of small objects
int morph_size = 2;
Mat element = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Rectangle, new System.Drawing.Size(2 * morph_size + 1, 2 * morph_size + 1), new System.Drawing.Point(morph_size, morph_size));
CvInvoke.MorphologyEx(segmentedImage, segmentedImage, Emgu.CV.CvEnum.MorphOp.Open, element, new System.Drawing.Point(-1, -1), 1, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar());

// Find edges that form rectangles
List<RotatedRect> boxList = new List<RotatedRect>();
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
    CvInvoke.FindContours(segmentedImage, contours, null, Emgu.CV.CvEnum.RetrType.External, ChainApproxMethod.ChainApproxSimple);
    int count = contours.Size;
    for (int i = 0; i < count; i++)
    {
        using (VectorOfPoint contour = contours[i])
        using (VectorOfPoint approxContour = new VectorOfPoint())
        {
            CvInvoke.ApproxPolyDP(contour, approxContour, CvInvoke.ArcLength(contour, true) * 0.01, true);
            if (CvInvoke.ContourArea(approxContour, false) > 10000)
            {
                if (approxContour.Size == 4)
                {
                    bool isRectangle = true;
                    System.Drawing.Point[] pts = approxContour.ToArray();
                    LineSegment2D[] edges = Emgu.CV.PointCollection.PolyLine(pts, true);
                    for (int j = 0; j < edges.Length; j++)
                    {
                        double angle = Math.Abs(edges[(j + 1) % edges.Length].GetExteriorAngleDegree(edges[j]));
                        if (angle < 80 || angle > 100)
                        {
                            isRectangle = false;
                            break;
                        }
                    }

                    if (isRectangle)
                    boxList.Add(CvInvoke.MinAreaRect(approxContour));
                }
            }
        }
    }
}

推荐答案

所以，如我所愿，我自己尝试了一下.在C ++中，但是Emgu应该很容易采用它.首先，我用一个开口消除了分割图像中的小物体:

So as promised i tried it myself. In C++ but you should adopt it easy to Emgu. First i get rid of small object in your segmented image with an opening:

int morph_elem = CV_SHAPE_RECT;
int morph_size = 2;
Mat element = getStructuringElement(morph_elem, Size(2 * morph_size + 1, 2 * morph_size + 1), Point(morph_size, morph_size));
// Apply the opening
morphologyEx(segmentedImage, segmentedImage_open, CV_MOP_OPEN, element);

然后检测所有轮廓并采用大轮廓并检查矩形:

Then detect all the contours and take the large ones and check for rectangular shape:

vector< vector<Point>> contours;
findContours(segmentedImage_open, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
    
for each (vector<Point> var in contours)
{
    double area = contourArea(var);
    if (area> 30000) 
    {
        vector<Point> approx;
        approxPolyDP(var, approx, 0.01*arcLength(var, true), true);
        
        if (4 == approx.size()) //rectangular shape 
        {
            // do something
        }
    }
}

这是轮廓为红色，近似曲线为绿色的结果:

Here is the result with the contour in red and the approximated curve in green:

您可以通过增加近似系数来改善代码，直到获得4点轮廓或超过阈值为止.只需在大约PolyPolyDP上包装一个for循环即可.您可以为近似值定义一个范围，并在对象与矩形的差异太大时防止代码失败.

You can improve your code by increasing the approximation factor until you get a contour with 4 points or you pass a threshold. Just wrap a for loop around approxPolyDP. You can define a range for your approximation value and prevent your code to fail if your object differs too much from a rectangle.

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