霍夫峰检测

时间:2018-08-16 23:44:49

标签: c# image-processing hough-transform

我已经实现了霍夫峰检测。输出如下:

enter image description here

我们可以看到RED线与画布的两侧(左,右)相交。

如何将检测到的行限制在源行的长度之间?

例如,

enter image description here

源代码

public class Line
{
    public Point Start { get; set; }
    public Point End { get; set; }

    public Line(Point start, Point end)
    {
        Start = start;
        End = end;
    }
}

public class HoughLineTransform
{
    public HoughMap Accumulator { get; set; }

    public HoughLineTransform()
    {
    }

    public List<Line> GetLines(int threshold)
    {
        if (Accumulator == null)
        {
            throw new Exception("HoughMap is null");
        }

        int houghWidth = Accumulator.Width;
        int houghHeight = Accumulator.Height;
        int imageWidth = Accumulator.Image.Width;
        int imageHeight = Accumulator.Image.Height;

        List<Line> lines = new List<Line>();

        if (Accumulator == null)
            return lines;

        for (int rho = 0; rho < houghWidth; rho++)
        {
            for (int theta = 0; theta < houghHeight; theta++)
            {
                if ((int)Accumulator[rho, theta] >= threshold)
                {
                    int peak = Accumulator[rho, theta];

                    for (int ly = -4; ly <= 4; ly++)
                    {
                        for (int lx = -4; lx <= 4; lx++)
                        {
                            if ((ly + rho >= 0 && ly + rho < houghWidth) && (lx + theta >= 0 && lx + theta < houghHeight))
                            {
                                if ((int)Accumulator[rho + ly, theta + lx] > peak)
                                {
                                    peak = Accumulator[rho + ly, theta + lx];
                                    ly = lx = 5;
                                }
                            }
                        }
                    }

                    if (peak > (int)Accumulator[rho, theta])
                        continue;

                    int x1, y1, x2, y2;
                    x1 = y1 = x2 = y2 = 0;

                    double rad = theta * Math.PI / 180;

                    if (theta >= 45 && theta <= 135)
                    {
                        x1 = 0;
                        y1 = (int)(((double)(rho - (houghWidth / 2)) - ((x1 - (imageWidth / 2)) * Math.Cos(rad))) / Math.Sin(rad) + (imageHeight / 2));
                        x2 = imageWidth - 0;
                        y2 = (int)(((double)(rho - (houghWidth / 2)) - ((x2 - (imageWidth / 2)) * Math.Cos(rad))) / Math.Sin(rad) + (imageHeight / 2));
                    }
                    else
                    {
                        y1 = 0;
                        x1 = (int)(((double)(rho - (houghWidth / 2)) - ((y1 - (imageHeight / 2)) * Math.Sin(rad))) / Math.Cos(rad) + (imageWidth / 2));
                        y2 = imageHeight - 0;
                        x2 = (int)(((double)(rho - (houghWidth / 2)) - ((y2 - (imageHeight / 2)) * Math.Sin(rad))) / Math.Cos(rad) + (imageWidth / 2));
                    }

                    lines.Add(new Line(new Point(x1, y1), new Point(x2, y2)));
                }
            }
        }

        return lines;
    }
}
  

相关:Hough Line Transform implementation

1 个答案:

答案 0 :(得分:1)

一种简单的方法是将所得的轮廓线叠加在原始图像上,并检查像素重叠的位置(具有特定的窗口)。

如果它们开始或结束重叠,则您具有线段的开始/结束。

顺便说一句:我还没有检查过您的算法,但是大约15年前我写了一个自己的书。我记得有一种迭代方法,您一次只能找到一行(只是累积图像中的最大值)。 找到一条线后,移除该线的累积像素,然后从找到最大值开始重新开始。 然后,找到第二重要的行。依此类推。