protected void fastHarrisRansacBlendStraight(List <Bitmap> imgs)
    {
        List <IntPoint[]> harrisPoints = new List <IntPoint[]>();
        MatrixH           homography;

        //Calculate all the Harris Points
        HarrisCornersDetector harris = new HarrisCornersDetector(0.03f, 10000f);

        for (int i = 0; i < imgs.Count; i++)
        {
            harrisPoints.Add(harris.ProcessImage(imgs[i]).ToArray());
        }

        Bitmap final = imgs[0];

        for (int i = 1; i < imgs.Count; i++)
        {
            //Convert my frames to grayscale so I can find and adjust the normal vectors
            AForge.Imaging.Filters.GrayscaleBT709 grayscale = new AForge.Imaging.Filters.GrayscaleBT709();
            AForge.Imaging.DocumentSkewChecker    skew      = new AForge.Imaging.DocumentSkewChecker();

            double finalAngle = skew.GetSkewAngle(grayscale.Apply(final));
            double imgAngle   = skew.GetSkewAngle(grayscale.Apply(imgs[i]));

            //Less than 5% to account for human error with rotations and wobbles
            if (Math.Abs(finalAngle - imgAngle) < 5)
            {
                AForge.Imaging.Filters.RotateBilinear rotate = new AForge.Imaging.Filters.RotateBilinear(finalAngle - imgAngle);
                rotate.FillColor = Color.FromArgb(0, 255, 255, 255);
                imgs[i]          = rotate.Apply(imgs[i]);

                //Update harris
                harrisPoints[i] = harris.ProcessImage(imgs[i]).ToArray();
            }

            IntPoint[] harrisFinal = harris.ProcessImage(final).ToArray();

            //Correlate the Harris pts between imgs
            CorrelationMatching matcher = new CorrelationMatching(5, final, imgs[i]);
            IntPoint[][]        matches = matcher.Match(harrisFinal, harrisPoints[i]);

            //Create the homography matrix using ransac
            RansacHomographyEstimator ransac = new RansacHomographyEstimator(0.025, 0.99);
            homography = ransac.Estimate(matches[0], matches[1]);

            Blend blend = new Blend(homography, final);
            blend.Gradient = true;
            final          = blend.Apply(imgs[i]);
        }

        showImage(final);
    }
    protected void surfRansacBlendStraight(List <Bitmap> imgs)
    {
        MatrixH homography;

        List <SpeededUpRobustFeaturePoint[]> surfPoints = new List <SpeededUpRobustFeaturePoint[]>();
        //Calculate all the Surf Points
        SpeededUpRobustFeaturesDetector surf = new SpeededUpRobustFeaturesDetector();
        double lastAngle = 0;

        for (int i = 0; i < imgs.Count; i++)
        {
            //Grayscale to find the edges and adjust the normal to point up
            AForge.Imaging.Filters.GrayscaleBT709 grayscale = new AForge.Imaging.Filters.GrayscaleBT709();
            AForge.Imaging.DocumentSkewChecker    skew      = new AForge.Imaging.DocumentSkewChecker();

            double angle = skew.GetSkewAngle(grayscale.Apply(imgs[i]));

            //Less than 5 deg change in angle to account for wobble, ignore big shifts
            if (Math.Abs(angle - lastAngle) < 5)
            {
                AForge.Imaging.Filters.RotateBilinear rotate = new AForge.Imaging.Filters.RotateBilinear(angle);
                rotate.FillColor = Color.FromArgb(0, 255, 255, 255);
                imgs[i]          = rotate.Apply(imgs[i]);
                lastAngle        = angle;
            }
            showImage(imgs[i]);
            surfPoints.Add(surf.ProcessImage(imgs[i]).ToArray());
        }


        Bitmap final = imgs[0];

        for (int i = 1; i < imgs.Count; i++)
        {
            SpeededUpRobustFeaturePoint[] surfFinal = surf.ProcessImage(final).ToArray();

            //Correlate the Harris pts between imgs
            KNearestNeighborMatching matcher = new KNearestNeighborMatching(5);
            matcher.Threshold = 0.05;

            IntPoint[][] matches = matcher.Match(surfFinal, surfPoints[i]);

            //Create the homography matrix using RANSAC
            RansacHomographyEstimator ransac = new RansacHomographyEstimator(0.015, 1);
            homography = ransac.Estimate(matches[0], matches[1]);

            Blend blend = new Blend(homography, final);
            blend.Gradient = true;
            final          = blend.Apply(imgs[i]);
        }

        //Smooth/Sharpen if I wanted to
        AForge.Imaging.Filters.Sharpen filter = new AForge.Imaging.Filters.Sharpen();
        //AForge.Imaging.Filters.Gaussian filter = new AForge.Imaging.Filters.Guassian(5);
        //filter.ApplyInPlace(final);

        showImage(final);
    }
        //1. bright pixel / dark pixel
        //2.lowest gray level
        //3.highest gray level
        //4.number of peaks in the x direction.
        //5.number of peaks in the y direction.
        public static double[] ExtractFeatures(Bitmap bmp,int i)
        {
            //Apply GrayScale
            GrayscaleBT709 greyScaleFilter = new GrayscaleBT709();
            Bitmap newBmp = greyScaleFilter.Apply((Bitmap)bmp.Clone());

            //Count Blobs
            BlobCounter blobCounter = new BlobCounter();
            blobCounter.BackgroundThreshold = Color.FromArgb(255, 150, 150, 150);
            blobCounter.ProcessImage(newBmp);
            int blobs = (blobCounter.ObjectsCount - 1) * 30;

            //Count Corner
            SusanCornersDetector scd = new SusanCornersDetector();
            scd.DifferenceThreshold = 70;
            scd.GeometricalThreshold = 8;
            int corners = scd.ProcessImage((Bitmap)newBmp.Clone()).Count();

            //Apply Edge Filter
            CannyEdgeDetector filter = new CannyEdgeDetector();
            //newBmp = filter.Apply(newBmp);
            Histogram his = new HorizontalIntensityStatistics(newBmp).Gray;
            Histogram vis = new VerticalIntensityStatistics(newBmp).Gray;

            HoughLineTransformation lineTransform = new HoughLineTransformation();
            // apply Hough line transofrm
            lineTransform.ProcessImage(filter.Apply(newBmp));
            Bitmap houghLineImage = lineTransform.ToBitmap();
            // get lines using relative intensity
            HoughLine[] lines = lineTransform.GetLinesByRelativeIntensity(1);
            int linesCount = lines.Count() * 30;

            double[] features = new double[13] { blobs, corners, his.Max, his.Min, his.Mean, his.Median, his.StdDev,
                vis.Max, vis.Min, vis.Mean, vis.Median, vis.StdDev,linesCount};

            //double[] features = new double[3] { blobs, corners,lines};

            newBmp.Save(String.Format("test{0}.bmp",i));
            return features;
        }
 private void Effect()
 {
     IFilter imgeFilter = new BurkesDithering();
     Bitmap bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnCommon.Image = bitimg;
     imgeFilter = new GrayscaleBT709();
     btnGray.Image = new Bitmap(imgeFilter.Apply(img), 90, 111);
     imgeFilter = new Sepia();
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnSeperia.Image = bitimg;
     imgeFilter = new Invert();
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnInvert.Image = bitimg;
     imgeFilter = new Blur();
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnBlur.Image = bitimg;
     imgeFilter = new Texturer(new AForge.Imaging.Textures.MarbleTexture(10, 11), 0.7f, 0.3f);
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnJitter.Image = bitimg;
     imgeFilter = new ChannelFiltering(new IntRange(0, 0), new IntRange(0, 255), new IntRange(0, 255));
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnCyan.Image = bitimg;
     imgeFilter = new YCbCrExtractChannel(AForge.Imaging.YCbCr.CrIndex);
     bitimg = new Bitmap(imgeFilter.Apply(img), 90, 111);
     btnBlackWhite.Image = bitimg;
 }
        /// <summary>
        /// Get rectangles objects in the image
        /// </summary>
        /// <param name="image">Image to get the rectangles</param>
        /// <param name="minWidth">Minimum width to consider as a valid rectangle</param>
        /// <param name="minHeight">Minimum height to consider as a valid ractangle</param>
        /// <returns>Return an array with the selected rectangle</returns>
        public Rectangle[] GetObjectsCoordinates(System.Drawing.Image image, int minWidth, int minHeight)
        {
            // create grayscale filter
            GrayscaleBT709 grayscaleFilter = new GrayscaleBT709();
            // apply it to color filtered image
            Bitmap grayImage = grayscaleFilter.Apply(new Bitmap(image));

            // create blob counter
            AForge.Imaging.BlobCounter blobCounter = new AForge.Imaging.BlobCounter();
            // configure it to filter out small objects
            blobCounter.MinWidth = minWidth;
            blobCounter.MinHeight = minHeight;
            blobCounter.FilterBlobs = true;
            // set ordering - bigger objects go first
            blobCounter.ObjectsOrder = AForge.Imaging.ObjectsOrder.YX;

            // locate blobs
            blobCounter.ProcessImage(grayImage);
            Rectangle[] rects = blobCounter.GetObjectsRectangles();
            return rects;
        }
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        public Bitmap Render()
        {
            if (this.IsReady == false)
                return null;

            Bitmap r = null;
            lock (this)
            {
                IFilter grayscaleFilter = new GrayscaleBT709();
                Bitmap b = grayscaleFilter.Apply(this.mBmp);
                r = new Bitmap(b.Width, b.Height);

                Graphics g = Graphics.FromImage(r);
                g.DrawImage(b, 0, 0, r.Width, r.Height);
                b.Dispose();

                if (this.ShowGrid)
                {
                    this.DrawGrid(g);
                }

                this.HighlightRegion(g, this.mBmp);

                this.DrawOutline(g);

                g.Dispose();
            }

            return r;
        }
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        private void traitementimage(ref Bitmap image)
        {

            ColorFiltering filter = new ColorFiltering();
            filter.Red = new IntRange(254, 255);
            filter.Green = new IntRange(0, 240);
            filter.Blue = new IntRange(0, 240);
            Bitmap tmp = filter.Apply(image);
            IFilter grayscale = new GrayscaleBT709();
            tmp = grayscale.Apply(tmp);
            BitmapData bitmapData = tmp.LockBits(new Rectangle(0, 0, image.Width, image.Height),
            ImageLockMode.ReadWrite, PixelFormat.Format8bppIndexed);
            BlobCounter blobCounter = new BlobCounter();
            blobCounter.ProcessImage(bitmapData);
            blobCounter.ObjectsOrder = ObjectsOrder.Size;
            Rectangle[] rects = blobCounter.GetObjectsRectangles();
            tmp.UnlockBits(bitmapData);
            tmp.Dispose();
            if (rects.Length != 0)
            {
                backpoint = Centre(rects[0]);
                lignes(ref image, backpoint);

            }

        }