C# open cv即emgu cv 定位車牌思路及代碼

最近沒什么事，了解圖像處理，所以學習了以下！由於我不太會C++，只能試着用C#編寫代碼！但是網上關於emgu cv的資料少之又少，而且很多還是英文的，而且講的不詳細。所以慢慢琢磨。寫了個c#定位車牌的代碼，不過效果不是很理想。參考了c++高手的代碼！

思路就是1.灰度化，豎向邊緣檢測

2.自適應二值化處理

3.形態學處理（膨脹和腐蝕）

4.輪廓查找與篩選

代碼如下：

            Image<Bgr, Byte> simage = img;    //new Image<Bgr, byte>("license-plate.jpg");
            //Image<Bgr, Byte> simage = sizeimage.Resize(400, 300, Emgu.CV.CvEnum.INTER.CV_INTER_NN);
            Image<Gray, Byte> GrayImg = new Image<Gray, Byte>(simage.Width, simage.Height);
            IntPtr GrayImg1 = CvInvoke.cvCreateImage(simage.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
            //灰度化
            CvInvoke.cvCvtColor(simage.Ptr, GrayImg1, Emgu.CV.CvEnum.COLOR_CONVERSION.BGR2GRAY);
            //首先創建一張16深度有符號的圖像區域
            IntPtr Sobel = CvInvoke.cvCreateImage(simage.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_16S, 1);
            //X方向的Sobel算子檢測
            CvInvoke.cvSobel(GrayImg1, Sobel, 2, 0, 3);
            IntPtr temp = CvInvoke.cvCreateImage(simage.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
            CvInvoke.cvConvertScale(Sobel, temp, 0.00390625, 0);
            ////int it = ComputeThresholdValue(GrayImg.ToBitmap());
            ////二值化處理
            ////Image<Gray, Byte> dest = GrayImg.ThresholdBinary(new Gray(it), new Gray(255));
            Image<Gray, Byte> dest = new Image<Gray, Byte>(simage.Width, simage.Height);
            //二值化處理
            CvInvoke.cvThreshold(temp, dest, 0, 255, Emgu.CV.CvEnum.THRESH.CV_THRESH_OTSU);
            IntPtr temp1 = CvInvoke.cvCreateImage(simage.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 1);
            Image<Gray, Byte> dest1 = new Image<Gray, Byte>(simage.Width, simage.Height);
            CvInvoke.cvCreateStructuringElementEx(3, 1, 1, 0, Emgu.CV.CvEnum.CV_ELEMENT_SHAPE.CV_SHAPE_RECT, temp1);
            CvInvoke.cvDilate(dest, dest1, temp1, 6);
            CvInvoke.cvErode(dest1, dest1, temp1, 7);
            CvInvoke.cvDilate(dest1, dest1, temp1, 1);
            CvInvoke.cvCreateStructuringElementEx(1, 3, 0, 1, Emgu.CV.CvEnum.CV_ELEMENT_SHAPE.CV_SHAPE_RECT, temp1);
            CvInvoke.cvErode(dest1, dest1, temp1, 2);
            CvInvoke.cvDilate(dest1, dest1, temp1, 2);
            IntPtr dst = CvInvoke.cvCreateImage(simage.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_8U, 3);
            CvInvoke.cvZero(dst);
            //dest.Dilate(10);
            //dest.Erode(5);
            using (MemStorage stor = new MemStorage())
            {
                Contour<Point> contours = dest1.FindContours(
                    Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
                    Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_CCOMP,
                    stor);
                for (; contours != null; contours = contours.HNext)
                {

                    Rectangle box = contours.BoundingRectangle;
                    Image<Bgr, Byte> test = simage.CopyBlank();
                    test.SetValue(255.0);
                    double whRatio = (double)box.Width / box.Height;
                    int area = (int)box.Width * box.Height;
                    if (area > 1000 && area<10000)
                    {
                        if ((3.0 < whRatio && whRatio < 6.0))
                        {
                            test.Draw(box, new Bgr(Color.Red), 2);
                            simage.Draw(box, new Bgr(Color.Red), 2);//CvInvoke.cvNamedWindow("dst");
                            //CvInvoke.cvShowImage("dst", dst);
                            imageBox1.Image = simage;
                        }
                    }
                }
            }

 

還是有一些細節沒處理好啊，希望大家能指點我這個新手