c# - opencvsharp を使用して画像内のテキストを認識する必要があります

Question

画像内のテキストを識別しようとしています。

実際には、画像内のテキスト位置を特定してテキストに変換しようとしています。

C++ で書かれたコードを見つけたので、それを C# に変換しようとしています。助けてください。

テキスト OpenCV の抽出

std::vector<cv::Rect> detectLetters(cv::Mat img)
{       std::vector<cv::Rect> boundRect;[enter image description here][1]
    cv::Mat img_gray, img_sobel, img_threshold, element;
    cvtColor(img, img_gray, CV_BGR2GRAY);
    cv::Sobel(img_gray, img_sobel, CV_8U, 1, 0, 3, 1, 0, cv::BORDER_DEFAULT);
    cv::threshold(img_sobel, img_threshold, 0, 255, CV_THRESH_OTSU+CV_THRESH_BINARY);
    element = getStructuringElement(cv::MORPH_RECT, cv::Size(10, 15) );
    cv::morphologyEx(img_threshold, img_threshold, CV_MOP_CLOSE, element); //Does the trick
    std::vector< std::vector< cv::Point> > contours;
    cv::findContours(img_threshold, contours, 0, 1); 
    std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
    for( int i = 0; i < contours.size(); i++ )
        if (contours[i].size()>80)
        { 
            cv::approxPolyDP( cv::Mat(contours[i]), contours_poly[i], 17, true );
            cv::Rect appRect( boundingRect( cv::Mat(contours_poly[i]) ));
            if (appRect.width>appRect.height) 
                boundRect.push_back(appRect);
        }
        return boundRect;
}

そして、それをC#に変換しようとしましたが、うまくいきませんでした

private List<Rectangle> detectLetters(IntPtr img)
{
    //cvtColor(img, img_gray, CV_BGR2GRAY);
    List<Rectangle> boundRect = new List<Rectangle>();

    //cv::Mat img_gray, img_sobel, img_threshold, element;
    IntPtr 
        img_gray = IntPtr.Zero, 
        img_sobel= IntPtr.Zero, 
        img_threshold= IntPtr.Zero,
        img_tmp = IntPtr.Zero,
        element= IntPtr.Zero;

    //cvtColor(img, img_gray, CV_BGR2GRAY);
    CvInvoke.cvCvtColor(img, img_gray,COLOR_CONVERSION.CV_BGR2GRAY); //CV_BGR2GRAY);

    //cv::Sobel(img_gray, img_sobel, CV_8U, 1, 0, 3, 1, 0, cv::BORDER_DEFAULT);
    CvInvoke.cvSobel(img_gray, img_sobel, 0, 1, 1);//, 3, 1, 0, cv.BORDER_DEFAULT);

    //cv.threshold(img_sobel, img_threshold, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
    CvInvoke.cvThreshold(img_sobel, img_threshold, 0, 255, THRESH.CV_THRESH_BINARY|THRESH.CV_THRESH_OTSU);

    //element = getStructuringElement(cv.MORPH_RECT, cv.Size(10, 15));
    element = CvInvoke.cvCreateStructuringElementEx(1,1,10,15,CV_ELEMENT_SHAPE.CV_SHAPE_RECT,element);// GetStructuringElement(

    //cv.morphologyEx(img_threshold, img_threshold, CV_MOP_CLOSE, element); //Does the trick
    CvInvoke.cvMorphologyEx(img_threshold,img_threshold,img_tmp,element,CV_MORPH_OP.CV_MOP_CLOSE,1);

    //List<List<cv.Point>> contours = new List<List<cv.Point>>();
    var contours = new List<IntPtr>();

    //cv.findContours(img_threshold, contours, 0, 1);
    CvInvoke.cvFindContours(img_threshold, element,ref ((IntPtr)contours[0]), 1, RETR_TYPE.CV_RETR_EXTERNAL, CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_NONE,new Point(0,0));


    //std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
    var contours_poly = new List<List<Point>>(contours.Count);

    //for( int i = 0; i < contours.size(); i++ )
    for (int i = 0; i < contours.Count; i++)
    {
        //if (contours[i].size()>80)
        if (contours[i].ToInt32() > 80)
        {
            //cv.approxPolyDP(Emgu.CV.Matrix<>(contours[i]), contours_poly[i], 17, true);
            CvInvoke.cvApproxPoly(contours[i], 17,contours_poly[i],APPROX_POLY_TYPE.CV_POLY_APPROX_DP, 1,1);
            //cv::Rect appRect( boundingRect( cv::Mat(contours_poly[i]) ));
            Rectangle appRect = new Rectangle(CvInvoke.cvBoundingRect(contours_poly[i],false));
            //if (appRect.width>appRect.height) 
            if (appRect.width > appRect.height)
            {
                //boundRect.push_back(appRect);
                boundRect.Add(appRect);
            }
        }
    }
    //return boundRect;
    return boundRect;
}