Question

我正在尝试实现一个在二进制图像中找到轮廓并过滤掉小轮廓的函数。

这是我的代码和示例图片。这是一个超级简单的功能，可以消除小区域的斑点。但我不断获得“边缘轮廓”而不是区域轮廓。：S

    private IplImage RemoveNoise( IplImage image, int minArea )
    {

        List<CvPoint[]> listOfPoints = new List<CvPoint[]>();

        CvSeq<CvPoint> contoursRaw;

        List<ContourData> contours = new List<ContourData>();
        using( CvMemStorage storage = new CvMemStorage() )
        {
            //find contoures
            //Cv.FindContours( image, storage, out contoursRaw );
            Cv.FindContours( image, storage, out contoursRaw, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple );
            //contoursRaw = Cv.ApproxPoly( contoursRaw, CvContour.SizeOf, storage, ApproxPolyMethod.DP, 3, true );

            while( contoursRaw != null )
            {
                CvSeq<CvPoint> result = contoursRaw;
                double area = Cv.ContourArea( result );

                //filter out small regions
                if( area >= minArea )
                {                   
                    List<CvPoint> points = new List<CvPoint>();
                    int i = 0;
                    while( result[ i ] != null )
                    {
                        points.Add( new CvPoint( result[ i ].Value.X, result[ i ].Value.Y ) );
                        i++;
                    }
                    listOfPoints.Add( points.ToArray() );

                }
                contoursRaw = contoursRaw.HNext;
            }
        }

        // draw large regions
        IplImage output = new IplImage( image.Size, image.Depth, 1 );
        output.Set( CvColor.Black );
        CvPoint[][] ArrayOfPoints = listOfPoints.ToArray();
        output.FillPoly( ArrayOfPoints, CvColor.White );

        return output;
    }

为什么我不断获得“边缘轮廓”而不是区域轮廓？

结果如下： enter image description here

Answer 1

试试这个。

IplImage input = new IplImage(@"C:\Users\20396600\Downloads\cont.jpg");
IplImage gray = new IplImage(input.Size, BitDepth.U8, 1);
IplImage invert = gray.Clone();
input.CvtColor(gray, ColorConversion.BgrToGray);
gray.Threshold(invert, 70, 255, ThresholdType.BinaryInv);
RemoveNoise(invert, 150);

private IplImage RemoveNoise(IplImage image, int minArea)
{
    IplImage output = new IplImage(image.Size, BitDepth.U8, 3);//image.Depth, 1);
    output.Set(CvColor.Black);
    CvSeq<CvPoint> contoursRaw;

    using (CvMemStorage storage = new CvMemStorage())
    {
        //find contours
        Cv.FindContours(image, storage, out contoursRaw, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple);

        //Taken straight from one of the OpenCvSharp samples
        using (CvContourScanner scanner = new CvContourScanner(image, storage, CvContour.SizeOf, ContourRetrieval.Tree, ContourChain.ApproxSimple))
        {
            foreach (CvSeq<CvPoint> c in scanner)
            {
                //Some contours are negative so make them all positive for easy comparison
                double area = Math.Abs(c.ContourArea());
                //Uncomment below to see the area of each contour
                //Console.WriteLine(area.ToString());
                if (area >= minArea)
                {
                    List<CvPoint[]> points = new List<CvPoint[]>();
                    List<CvPoint> point = new List<CvPoint>();
                    foreach (CvPoint p in c.ToArray())
                        point.Add(p);

                    points.Add(point.ToArray());

                    //Use FillPoly instead of DrawContours as requested
                    output.FillPoly(points.ToArray(), CvColor.Red, LineType.AntiAlias);

                    //-1 means fill the polygon
                    //output.DrawContours(c, CvColor.White, CvColor.Green, 0, -1, LineType.AntiAlias);

                    //Uncomment two lines below to see contours being drawn gradually
                    //Cv.ShowImage("Window", output);
                    //Cv.WaitKey();
                }
            }
        } 
    }
    output.SaveImage("output.png");

    return output;
}

基于这里的解释请求是秘密酱。

反转图像有助于正确找到轮廓。 FindContour希望在黑色背景上找到白色物体。
ContourArea（）返回负值，因此Math.Abs（）有助于过滤到您想要的内容。
如果-1作为厚度传递，DrawContour（）函数将填充轮廓。

其他所有内容与OpenCvSharp下载中提供的样本非常相似。希望这会有所帮助。

编辑：通过另一个频道，作者要求能够使用FillPoly而不是DrawContours，因此示例代码已经更新以反映出来。

OpenCVSharp的findContour返回错误的数据

1 个答案: