emgu比对.txt

 private void button43_Click(object sender, EventArgs e)
        {
            Mat baseMat = new Mat();
            Mat detectedMat = new Mat();
            if (chapter1OFD.ShowDialog() == System.Windows.Forms.DialogResult.OK)
                baseMat = CvInvoke.Imread(chapter1OFD.FileName, LoadImageType.AnyColor | LoadImageType.AnyColor);
            //获取基准图像,该图像用来获得狒狒脸部ROI  
            if (baseMat.IsEmpty | baseMat.NumberOfChannels != 3)
                return;
            var rect = new System.Drawing.Rectangle(113, 252, 35, 40);
            var tempImg = baseMat.Clone();
            CvInvoke.NamedWindow("baseImage", NamedWindowType.KeepRatio);
            CvInvoke.Rectangle(tempImg, rect, new MCvScalar(0, 0, 255), 2);
            CvInvoke.Imshow("baseImage", tempImg);
            //显示基准图像，并标出ROI区域 
            var imgROI = new Mat(baseMat, rect);
            //狒狒脸部ROI  
            //屏蔽饱和度过低的像素,得到掩码mask 
            int minSat = 65;
            var hsvROI = new Mat();
            CvInvoke.CvtColor(imgROI, hsvROI, ColorConversion.Bgr2Hsv);
            var hsvROIImg = hsvROI.ToImage<Hsv, byte>();
            var mask = new Mat();
            CvInvoke.Threshold(hsvROIImg.Split()[1], mask, minSat, 255, ThresholdType.Binary);
            //得到ROI色调直方图，mask中的像素没有参与计算  
            DenseHistogram hist = new DenseHistogram(181, new RangeF(0f, 180.1f));
            hist.Calculate<byte>(new Image<Gray, byte>[] { hsvROIImg.Split()[0] }, false, mask.ToImage<Gray, byte>());
            //获取将要检测的图像，并对HSV图像中的色调图像反投影  
            if (chapter1OFD.ShowDialog() == System.Windows.Forms.DialogResult.OK)
                detectedMat = CvInvoke.Imread(chapter1OFD.FileName, LoadImageType.AnyColor | LoadImageType.AnyColor);
            //获取图像    
          if (detectedMat.IsEmpty | detectedMat.NumberOfChannels != 3)
                return;
            var hsvMat = new Mat();
            CvInvoke.CvtColor(detectedMat, hsvMat, ColorConversion.Bgr2Hsv);
            //获取HSV数据 
            var resultImg = hist.BackProject<byte>(new Image<Gray, byte>[] { hsvMat.ToImage<Hsv, byte>().Split()[0] });
            var criteria = new MCvTermCriteria(1000, 0.01);
            CvInvoke.MeanShift(resultImg, ref rect, criteria);
            //均值偏移，计算得到脸部区域 
            tempImg = detectedMat.Clone();
            CvInvoke.Rectangle(tempImg, rect, new MCvScalar(255, 0, 0), 2);
            CvInvoke.NamedWindow("detectedImage", NamedWindowType.KeepRatio);
            CvInvoke.Imshow("detectedImage", tempImg);
        }