环境：Win8 64位 Vs2015

Emgu 版本：emgucv-windesktop 3.2.0.2682

上图为常用阈值化处理效果。不同阈值设置可呈现不同处理效果。

       private void InitSourceFile(object sender, RoutedEventArgs e){string sFile = "";if (!String.IsNullOrEmpty(AppConstUtils.GDefaultFile) && File.Exists(AppConstUtils.GDefaultFile))sFile = AppConstUtils.GDefaultFile;elsesFile = GlobalVar.DATAS_PATH + "Samples/Test3.png";BitmapImage oOriginBitSrc = new BitmapImage(new Uri(sFile));this.ImgOrigin1Zm.Source = oOriginBitSrc;System.Drawing.Image oImgOrigin = System.Drawing.Image.FromFile(sFile);System.Drawing.Bitmap oBitmap = new System.Drawing.Bitmap(oImgOrigin);Image<Bgr, byte> imgSrc = new Image<Bgr, byte>(oBitmap);oBitmap.Dispose();this.Func1(imgSrc);this.Func2(imgSrc);this.Func3(imgSrc);this.Func4(imgSrc);this.Func5(imgSrc);}private void Func1(Image<Bgr, byte> imgSrc){// 灰度化Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);AppUtils.ShowGrayImage(this.ImgFun1Result1Zm, imgGray);// 转换为BitmapSource呈现// 二进制阈值化Image<Gray, byte> imgThresholdBinary = new Image<Gray, byte>(imgGray.Size);//90为阈值,可调整，255为最大值CvInvoke.Threshold(imgGray, imgThresholdBinary, 90, 255, ThresholdType.Binary);AppUtils.ShowGrayImage(this.ImgFun1Result2Zm, imgThresholdBinary);//反向二进制阈值化Image<Gray, byte> imgThresholdBinaryInv = new Image<Gray, byte>(imgGray.Size); CvInvoke.Threshold(imgGray, imgThresholdBinaryInv, 90, 255, ThresholdType.BinaryInv);AppUtils.ShowGrayImage(this.ImgFun1Result3Zm, imgThresholdBinaryInv);//截断阈值化Image<Gray, byte> imgThresholdTrunc = new Image<Gray, byte>(imgGray.Size);CvInvoke.Threshold(imgGray, imgThresholdTrunc, 90, 255, ThresholdType.Trunc);AppUtils.ShowGrayImage(this.ImgFun1Result4Zm, imgThresholdTrunc);//超阈值归零化Image<Gray, byte> imgThresholdToZero = new Image<Gray, byte>(imgGray.Size);CvInvoke.Threshold(imgGray, imgThresholdToZero, 90, 255, ThresholdType.ToZero);AppUtils.ShowGrayImage(this.ImgFun1Result5Zm, imgThresholdToZero);//低于阈值归零化Image<Gray, byte> imgThresholdToZeroInv = new Image<Gray, byte>(imgGray.Size);CvInvoke.Threshold(imgGray, imgThresholdToZeroInv, 150, 255, ThresholdType.ToZeroInv);AppUtils.ShowGrayImage(this.ImgFun1Result6Zm, imgThresholdToZeroInv);//MaskImage<Gray, byte> imgThresholdMask = new Image<Gray, byte>(imgGray.Size);CvInvoke.Threshold(imgGray, imgThresholdMask, 90, 255, ThresholdType.Mask);AppUtils.ShowGrayImage(this.ImgFun1Result7Zm, imgThresholdMask);//OtsuImage<Gray, byte> imgThresholdOtsu = new Image<Gray, byte>(imgGray.Size);CvInvoke.Threshold(imgGray, imgThresholdOtsu, 150, 255, ThresholdType.Otsu);AppUtils.ShowGrayImage(this.ImgFun1Result8Zm, imgThresholdOtsu);}private void Func2(Image<Bgr, byte> imgSrc){// 灰度化Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);// 自适应阈值Image<Gray, byte> imgAdapativeThresholdMeanC = imgGray.ThresholdAdaptive(new Gray(255), AdaptiveThresholdType.MeanC, ThresholdType.Binary, 9, new Gray(5));AppUtils.ShowGrayImage(this.ImgFun2Result1Zm, imgAdapativeThresholdMeanC);}private void Func3(Image<Bgr, byte> imgSrc){// 灰度化Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);// 自适应阈值Image<Gray, byte> imgAdapativeThresholdGaussianC = imgGray.ThresholdAdaptive(new Gray(255),AdaptiveThresholdType.GaussianC, ThresholdType.Binary, 9, new Gray(5));AppUtils.ShowGrayImage(this.ImgFun2Result2Zm, imgAdapativeThresholdGaussianC);}private void Func4(Image<Bgr, byte> imgSrc){// 灰度化Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);// 自适应阈值Image<Gray, byte> imgAdapativeThresholdMeanC = imgGray.ThresholdAdaptive(new Gray(255),AdaptiveThresholdType.MeanC, ThresholdType.BinaryInv, 9, new Gray(5));AppUtils.ShowGrayImage(this.ImgFun2Result3Zm, imgAdapativeThresholdMeanC);}private void Func5(Image<Bgr, byte> imgSrc){// 灰度化Image<Gray, byte> imgGray = new Image<Gray, byte>(imgSrc.Size);CvInvoke.CvtColor(imgSrc, imgGray, ColorConversion.Bgr2Gray);// 自适应阈值Image<Gray, byte> imgAdapativeThresholdGaussianC = imgGray.ThresholdAdaptive(new Gray(255),AdaptiveThresholdType.GaussianC, ThresholdType.BinaryInv, 9, new Gray(5));AppUtils.ShowGrayImage(this.ImgFun2Result4Zm, imgAdapativeThresholdGaussianC);}

另外：

 AppUtils.ShowGrayImage(Image oImg, Image<Bgr, byte> imgSrc); 在我的上一篇博客中有实现。

点击打开链接  http://blog.csdn.net/u013224722/article/details/79613445