Exemple #1
0
        public static void FindMatch(Image <Gray, Byte> modelImage, Image <Gray, byte> observedImage, out long matchTime, out VectorOfKeyPoint modelKeyPoints, out VectorOfKeyPoint observedKeyPoints, out Matrix <int> indices, out Matrix <byte> mask, out HomographyMatrix homography)
        {
            int          k = 2;
            double       uniquenessThreshold = 0.8;
            SURFDetector surfCPU             = new SURFDetector(500, false);
            Stopwatch    watch;

            homography = null;

            if (GpuInvoke.HasCuda)
            {
                GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
                using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
                    //extract features from the object image
                    using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
                        using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
                            using (GpuBruteForceMatcher <float> matcher = new GpuBruteForceMatcher <float>(DistanceType.L2))
                            {
                                modelKeyPoints = new VectorOfKeyPoint();
                                surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
                                watch = Stopwatch.StartNew();

                                // extract features from the observed image
                                using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
                                    using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
                                        using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                    using (GpuMat <Byte> gpuMask = new GpuMat <byte>(gpuMatchIndices.Size.Height, 1, 1))
                                                        using (Stream stream = new Stream())
                                                        {
                                                            matcher.KnnMatchSingle(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, k, null, stream);
                                                            indices = new Matrix <int>(gpuMatchIndices.Size);
                                                            mask    = new Matrix <byte>(gpuMask.Size);

                                                            //gpu implementation of voteForUniquess
                                                            using (GpuMat <float> col0 = gpuMatchDist.Col(0))
                                                                using (GpuMat <float> col1 = gpuMatchDist.Col(1))
                                                                {
                                                                    GpuInvoke.Multiply(col1, new MCvScalar(uniquenessThreshold), col1, stream);
                                                                    GpuInvoke.Compare(col0, col1, gpuMask, CMP_TYPE.CV_CMP_LE, stream);
                                                                }

                                                            observedKeyPoints = new VectorOfKeyPoint();
                                                            surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);

                                                            //wait for the stream to complete its tasks
                                                            //We can perform some other CPU intesive stuffs here while we are waiting for the stream to complete.
                                                            stream.WaitForCompletion();

                                                            gpuMask.Download(mask);
                                                            gpuMatchIndices.Download(indices);

                                                            if (GpuInvoke.CountNonZero(gpuMask) >= 4)
                                                            {
                                                                int nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                                                                if (nonZeroCount >= 4)
                                                                {
                                                                    homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                                                                }
                                                            }

                                                            watch.Stop();
                                                        }
                            }
            }
            else
            {
                //extract features from the object image
                modelKeyPoints = new VectorOfKeyPoint();
                Matrix <float> modelDescriptors = surfCPU.DetectAndCompute(modelImage, null, modelKeyPoints);

                watch = Stopwatch.StartNew();

                // extract features from the observed image
                observedKeyPoints = new VectorOfKeyPoint();
                Matrix <float>            observedDescriptors = surfCPU.DetectAndCompute(observedImage, null, observedKeyPoints);
                BruteForceMatcher <float> matcher             = new BruteForceMatcher <float>(DistanceType.L2);
                matcher.Add(modelDescriptors);

                indices = new Matrix <int>(observedDescriptors.Rows, k);
                using (Matrix <float> dist = new Matrix <float>(observedDescriptors.Rows, k))
                {
                    matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
                    mask = new Matrix <byte>(dist.Rows, 1);
                    mask.SetValue(255);
                    Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
                }

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 4)
                {
                    nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 4)
                    {
                        homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                    }
                }

                watch.Stop();
            }
            matchTime = watch.ElapsedMilliseconds;
        }
        private Image <Bgr, byte> Match(Image <Bgr, byte> image1, Image <Bgr, byte> image2, int flag)
        {
            HomographyMatrix homography      = null;
            SURFDetector     surfDetectorCPU = new SURFDetector(500, false);

            int    k = 2;           //number of matches that we want ot find between image1 and image2
            double uniquenessThreshold = 0.8;

            Matrix <int>  indices;
            Matrix <byte> mask;

            VectorOfKeyPoint KeyPointsImage1;
            VectorOfKeyPoint KeyPointsImage2;

            Image <Gray, Byte> Image1G = image1.Convert <Gray, Byte>();
            Image <Gray, Byte> Image2G = image2.Convert <Gray, Byte>();

            if (GpuInvoke.HasCuda)      //Using CUDA, the GPUs can be used for general purpose processing (i.e., not exclusively graphics), speed up performance
            {
                Console.WriteLine("Here");
                GpuSURFDetector surfDetectorGPU = new GpuSURFDetector(surfDetectorCPU.SURFParams, 0.01f);

                // extract features from Image1
                using (GpuImage <Gray, Byte> gpuImage1 = new GpuImage <Gray, byte>(Image1G))                                                     //convert CPU input image to GPUImage(greyscale)
                    using (GpuMat <float> gpuKeyPointsImage1 = surfDetectorGPU.DetectKeyPointsRaw(gpuImage1, null))                              //find key points for image
                        using (GpuMat <float> gpuDescriptorsImage1 = surfDetectorGPU.ComputeDescriptorsRaw(gpuImage1, null, gpuKeyPointsImage1)) //calculate descriptor for each key point
                            using (GpuBruteForceMatcher <float> matcher = new GpuBruteForceMatcher <float>(DistanceType.L2))                     //create a new matcher object
                            {
                                KeyPointsImage1 = new VectorOfKeyPoint();
                                surfDetectorGPU.DownloadKeypoints(gpuKeyPointsImage1, KeyPointsImage1);                                 //copy the Matrix from GPU to CPU

                                // extract features from Image2
                                using (GpuImage <Gray, Byte> gpuImage2 = new GpuImage <Gray, byte>(Image2G))
                                    using (GpuMat <float> gpuKeyPointsImage2 = surfDetectorGPU.DetectKeyPointsRaw(gpuImage2, null))
                                        using (GpuMat <float> gpuDescriptorsImage2 = surfDetectorGPU.ComputeDescriptorsRaw(gpuImage2, null, gpuKeyPointsImage2))

                                            //for each descriptor of each image2 , we find k best matching points and their distances from image1 descriptors

                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuDescriptorsImage2.Size.Height, k, 1, true))      //stores indices of k best mathces
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuDescriptorsImage2.Size.Height, k, 1, true)) //stores distance of k best matches

                                                    using (GpuMat <Byte> gpuMask = new GpuMat <byte>(gpuMatchIndices.Size.Height, 1, 1))               //stores result of comparison
                                                        using (Stream stream = new Stream())
                                                        {
                                                            matcher.KnnMatchSingle(gpuDescriptorsImage2, gpuDescriptorsImage1, gpuMatchIndices, gpuMatchDist, k, null, stream); //matching descriptors of image2 to image1 and storing the k best indices and corresponding distances

                                                            indices = new Matrix <int>(gpuMatchIndices.Size);
                                                            mask    = new Matrix <byte>(gpuMask.Size);

                                                            //gpu implementation of voteForUniquess
                                                            using (GpuMat <float> col0 = gpuMatchDist.Col(0))
                                                                using (GpuMat <float> col1 = gpuMatchDist.Col(1))
                                                                {
                                                                    GpuInvoke.Multiply(col1, new MCvScalar(uniquenessThreshold), col1, stream); //by setting stream, we perform an Async Task
                                                                    GpuInvoke.Compare(col0, col1, gpuMask, CMP_TYPE.CV_CMP_LE, stream);         //col0 >= 0.8col1 , only then is it considered a good match
                                                                }

                                                            KeyPointsImage2 = new VectorOfKeyPoint();
                                                            surfDetectorGPU.DownloadKeypoints(gpuKeyPointsImage2, KeyPointsImage2);

                                                            //wait for the stream to complete its tasks
                                                            //We can perform some other CPU intesive stuffs here while we are waiting for the stream to complete.
                                                            stream.WaitForCompletion();

                                                            gpuMask.Download(mask);
                                                            gpuMatchIndices.Download(indices);

                                                            if (GpuInvoke.CountNonZero(gpuMask) >= 4)
                                                            {
                                                                int nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(KeyPointsImage1, KeyPointsImage2, indices, mask, 1.5, 20); //count the number of nonzero points in the mask(this stored the comparison result of col0 >= 0.8col1)
                                                                //we can create a homography matrix only if we have atleast 4 matching points
                                                                if (nonZeroCount >= 4)
                                                                {
                                                                    homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(KeyPointsImage1, KeyPointsImage2, indices, mask, 2);
                                                                }
                                                            }
                                                        }
                            }
            }
            else
            {
                Console.WriteLine("No CUDA");
                //extract features from image2
                KeyPointsImage1 = new VectorOfKeyPoint();
                Matrix <float> DescriptorsImage1 = surfDetectorCPU.DetectAndCompute(Image1G, null, KeyPointsImage1);

                //extract features from image1
                KeyPointsImage2 = new VectorOfKeyPoint();
                Matrix <float>            DescriptorsImage2 = surfDetectorCPU.DetectAndCompute(Image2G, null, KeyPointsImage2);
                BruteForceMatcher <float> matcher           = new BruteForceMatcher <float>(DistanceType.L2);
                matcher.Add(DescriptorsImage1);

                indices = new Matrix <int>(DescriptorsImage2.Rows, k);
                using (Matrix <float> dist = new Matrix <float>(DescriptorsImage2.Rows, k))
                {
                    matcher.KnnMatch(DescriptorsImage2, indices, dist, k, null);
                    mask = new Matrix <byte>(dist.Rows, 1);
                    mask.SetValue(255);
                    Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
                }

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 4)
                {
                    nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(KeyPointsImage1, KeyPointsImage2, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 4)
                    {
                        homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(KeyPointsImage1, KeyPointsImage2, indices, mask, 2);
                    }
                }
            }
            Image <Bgr, Byte> mImage = image1.Convert <Bgr, Byte>();
            Image <Bgr, Byte> oImage = image2.Convert <Bgr, Byte>();
            Image <Bgr, Byte> result = new Image <Bgr, byte>(mImage.Width + oImage.Width, mImage.Height);

            //Image<Bgr, Byte> temp = Features2DToolbox.DrawMatches(image1, KeyPointsImage1, image2, KeyPointsImage2, indices, new Bgr(255, 255, 255), new Bgr(255, 255, 255), mask, Features2DToolbox.KeypointDrawType.DEFAULT);

            if (homography != null)
            {  //draw a rectangle along the projected model
                Rectangle rect = image1.ROI;
                PointF[]  pts  = new PointF[] {
                    new PointF(rect.Left, rect.Bottom),
                    new PointF(rect.Right, rect.Bottom),
                    new PointF(rect.Right, rect.Top),
                    new PointF(rect.Left, rect.Top)
                };

                homography.ProjectPoints(pts);

                HomographyMatrix origin = new HomographyMatrix();                //I perform a copy of the left image with a not real shift operation on the origin
                origin.SetIdentity();
                origin.Data[0, 2] = 0;
                origin.Data[1, 2] = 0;
                Image <Bgr, Byte> mosaic = new Image <Bgr, byte>(mImage.Width + oImage.Width, mImage.Height * 2);

                Image <Bgr, byte> warp_image = mosaic.Clone();
                mosaic = mImage.WarpPerspective(origin, mosaic.Width, mosaic.Height, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR, Emgu.CV.CvEnum.WARP.CV_WARP_DEFAULT, new Bgr(0, 0, 0));

                warp_image = oImage.WarpPerspective(homography, warp_image.Width, warp_image.Height, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR, Emgu.CV.CvEnum.WARP.CV_WARP_INVERSE_MAP, new Bgr(200, 0, 0));
                Image <Gray, byte> warp_image_mask = oImage.Convert <Gray, byte>();
                warp_image_mask.SetValue(new Gray(255));
                Image <Gray, byte> warp_mosaic_mask = mosaic.Convert <Gray, byte>();
                warp_mosaic_mask.SetZero();
                warp_mosaic_mask = warp_image_mask.WarpPerspective(homography, warp_mosaic_mask.Width, warp_mosaic_mask.Height, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR, Emgu.CV.CvEnum.WARP.CV_WARP_INVERSE_MAP, new Gray(0));

                warp_image.Copy(mosaic, warp_mosaic_mask);
                if (flag == 1)
                {
                    Console.WriteLine("Using Image Blending");
                    return(blend(mosaic, warp_image, warp_mosaic_mask, 2));
                }
                else
                {
                    Console.WriteLine("No Image Blending");
                    return(mosaic);
                }
            }
            return(null);
        }
Exemple #3
0
        /// <summary>
        /// Draw the model image and observed image, the matched features and homography projection.
        /// </summary>
        /// <param name="modelImage">The model image</param>
        /// <param name="observedImage">The observed image</param>
        /// <param name="matchTime">The output total time for computing the homography matrix.</param>
        /// <returns>The model image and observed image, the matched features and homography projection.</returns>
        public static Image <Bgr, Byte> Draw(Image <Gray, Byte> modelImage, Image <Gray, byte> observedImage, out long matchTime)
        {
            Stopwatch        watch;
            HomographyMatrix homography = null;

            SURFDetector     surfCPU = new SURFDetector(500, false);
            VectorOfKeyPoint modelKeyPoints;
            VectorOfKeyPoint observedKeyPoints;
            Matrix <int>     indices;

            Matrix <byte> mask;
            int           k = 2;
            double        uniquenessThreshold = 0.8;

            if (GpuInvoke.HasCuda)
            {
                GpuSURFDetector surfGPU = new GpuSURFDetector(surfCPU.SURFParams, 0.01f);
                using (GpuImage <Gray, Byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
                    //extract features from the object image
                    using (GpuMat <float> gpuModelKeyPoints = surfGPU.DetectKeyPointsRaw(gpuModelImage, null))
                        using (GpuMat <float> gpuModelDescriptors = surfGPU.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
                            using (GpuBruteForceMatcher <float> matcher = new GpuBruteForceMatcher <float>(DistanceType.L2))
                            {
                                modelKeyPoints = new VectorOfKeyPoint();
                                surfGPU.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);
                                watch = Stopwatch.StartNew();

                                // extract features from the observed image
                                using (GpuImage <Gray, Byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
                                    using (GpuMat <float> gpuObservedKeyPoints = surfGPU.DetectKeyPointsRaw(gpuObservedImage, null))
                                        using (GpuMat <float> gpuObservedDescriptors = surfGPU.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                    using (GpuMat <Byte> gpuMask = new GpuMat <byte>(gpuMatchIndices.Size.Height, 1, 1))
                                                        using (Stream stream = new Stream())
                                                        {
                                                            matcher.KnnMatchSingle(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, k, null, stream);
                                                            indices = new Matrix <int>(gpuMatchIndices.Size);
                                                            mask    = new Matrix <byte>(gpuMask.Size);

                                                            //gpu implementation of voteForUniquess
                                                            using (GpuMat <float> col0 = gpuMatchDist.Col(0))
                                                                using (GpuMat <float> col1 = gpuMatchDist.Col(1))
                                                                {
                                                                    GpuInvoke.Multiply(col1, new MCvScalar(uniquenessThreshold), col1, stream);
                                                                    GpuInvoke.Compare(col0, col1, gpuMask, CMP_TYPE.CV_CMP_LE, stream);
                                                                }

                                                            observedKeyPoints = new VectorOfKeyPoint();
                                                            surfGPU.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);

                                                            //wait for the stream to complete its tasks
                                                            //We can perform some other CPU intesive stuffs here while we are waiting for the stream to complete.
                                                            stream.WaitForCompletion();

                                                            gpuMask.Download(mask);
                                                            gpuMatchIndices.Download(indices);

                                                            if (GpuInvoke.CountNonZero(gpuMask) >= 4)
                                                            {
                                                                int nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                                                                if (nonZeroCount >= 4)
                                                                {
                                                                    homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                                                                }
                                                            }

                                                            watch.Stop();
                                                        }
                            }
            }
            else
            {
                //extract features from the object image
                modelKeyPoints = surfCPU.DetectKeyPointsRaw(modelImage, null);
                Matrix <float> modelDescriptors = surfCPU.ComputeDescriptorsRaw(modelImage, null, modelKeyPoints);

                watch = Stopwatch.StartNew();

                // extract features from the observed image
                observedKeyPoints = surfCPU.DetectKeyPointsRaw(observedImage, null);
                Matrix <float>            observedDescriptors = surfCPU.ComputeDescriptorsRaw(observedImage, null, observedKeyPoints);
                BruteForceMatcher <float> matcher             = new BruteForceMatcher <float>(DistanceType.L2);
                matcher.Add(modelDescriptors);

                indices = new Matrix <int>(observedDescriptors.Rows, k);
                using (Matrix <float> dist = new Matrix <float>(observedDescriptors.Rows, k))
                {
                    matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
                    mask = new Matrix <byte>(dist.Rows, 1);
                    mask.SetValue(255);
                    Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
                }

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 4)
                {
                    nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 4)
                    {
                        homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                    }
                }

                watch.Stop();
            }

            //Draw the matched keypoints
            Image <Bgr, Byte> result = Features2DToolbox.DrawMatches(modelImage, modelKeyPoints, observedImage, observedKeyPoints,
                                                                     indices, new Bgr(255, 255, 255), new Bgr(255, 255, 255), mask, Features2DToolbox.KeypointDrawType.DEFAULT);

            #region draw the projected region on the image
            if (homography != null)
            {  //draw a rectangle along the projected model
                Rectangle rect = modelImage.ROI;
                PointF[]  pts  = new PointF[] {
                    new PointF(rect.Left, rect.Bottom),
                    new PointF(rect.Right, rect.Bottom),
                    new PointF(rect.Right, rect.Top),
                    new PointF(rect.Left, rect.Top)
                };
                homography.ProjectPoints(pts);

                result.DrawPolyline(Array.ConvertAll <PointF, Point>(pts, Point.Round), true, new Bgr(Color.Red), 5);
            }
            #endregion

            matchTime = watch.ElapsedMilliseconds;

            return(result);
        }
Exemple #4
0
        public static bool FindModelImageInObservedImage(Image <Gray, byte> modelImage, Image <Gray, byte> observedImage)
        {
            var surfCpu = new SURFDetector(500, false);
            VectorOfKeyPoint modelKeyPoints;
            VectorOfKeyPoint observedKeyPoints;
            Matrix <int>     indices;

            Matrix <byte> mask;
            int           k = 2;
            double        uniquenessThreshold = 0.8;

            if (GpuInvoke.HasCuda)
            {
                GpuSURFDetector surfGpu = new GpuSURFDetector(surfCpu.SURFParams, 0.01f);
                using (GpuImage <Gray, byte> gpuModelImage = new GpuImage <Gray, byte>(modelImage))
                    //extract features from the object image
                    using (GpuMat <float> gpuModelKeyPoints = surfGpu.DetectKeyPointsRaw(gpuModelImage, null))
                        using (GpuMat <float> gpuModelDescriptors = surfGpu.ComputeDescriptorsRaw(gpuModelImage, null, gpuModelKeyPoints))
                            using (GpuBruteForceMatcher <float> matcher = new GpuBruteForceMatcher <float>(DistanceType.L2))
                            {
                                modelKeyPoints = new VectorOfKeyPoint();
                                surfGpu.DownloadKeypoints(gpuModelKeyPoints, modelKeyPoints);

                                // extract features from the observed image
                                using (GpuImage <Gray, byte> gpuObservedImage = new GpuImage <Gray, byte>(observedImage))
                                    using (GpuMat <float> gpuObservedKeyPoints = surfGpu.DetectKeyPointsRaw(gpuObservedImage, null))
                                        using (GpuMat <float> gpuObservedDescriptors = surfGpu.ComputeDescriptorsRaw(gpuObservedImage, null, gpuObservedKeyPoints))
                                            using (GpuMat <int> gpuMatchIndices = new GpuMat <int>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                using (GpuMat <float> gpuMatchDist = new GpuMat <float>(gpuObservedDescriptors.Size.Height, k, 1, true))
                                                    using (GpuMat <Byte> gpuMask = new GpuMat <byte>(gpuMatchIndices.Size.Height, 1, 1))
                                                        using (var stream = new Emgu.CV.GPU.Stream())
                                                        {
                                                            matcher.KnnMatchSingle(gpuObservedDescriptors, gpuModelDescriptors, gpuMatchIndices, gpuMatchDist, k, null, stream);
                                                            indices = new Matrix <int>(gpuMatchIndices.Size);
                                                            mask    = new Matrix <byte>(gpuMask.Size);

                                                            //gpu implementation of voteForUniquess
                                                            using (GpuMat <float> col0 = gpuMatchDist.Col(0))
                                                                using (GpuMat <float> col1 = gpuMatchDist.Col(1))
                                                                {
                                                                    GpuInvoke.Multiply(col1, new MCvScalar(uniquenessThreshold), col1, stream);
                                                                    GpuInvoke.Compare(col0, col1, gpuMask, CMP_TYPE.CV_CMP_LE, stream);
                                                                }

                                                            observedKeyPoints = new VectorOfKeyPoint();
                                                            surfGpu.DownloadKeypoints(gpuObservedKeyPoints, observedKeyPoints);

                                                            //wait for the stream to complete its tasks
                                                            //We can perform some other CPU intesive stuffs here while we are waiting for the stream to complete.
                                                            stream.WaitForCompletion();

                                                            gpuMask.Download(mask);
                                                            gpuMatchIndices.Download(indices);

                                                            if (GpuInvoke.CountNonZero(gpuMask) >= 4)
                                                            {
                                                                int nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                                                                if (nonZeroCount >= 4)
                                                                {
                                                                    Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                                                                }
                                                                if ((double)nonZeroCount / mask.Height > 0.02)
                                                                {
                                                                    return(true);
                                                                }
                                                            }
                                                        }
                            }
            }
            else
            {
                //extract features from the object image
                modelKeyPoints = surfCpu.DetectKeyPointsRaw(modelImage, null);
                Matrix <float> modelDescriptors = surfCpu.ComputeDescriptorsRaw(modelImage, null, modelKeyPoints);

                // extract features from the observed image
                observedKeyPoints = surfCpu.DetectKeyPointsRaw(observedImage, null);
                Matrix <float>            observedDescriptors = surfCpu.ComputeDescriptorsRaw(observedImage, null, observedKeyPoints);
                BruteForceMatcher <float> matcher             = new BruteForceMatcher <float>(DistanceType.L2);
                matcher.Add(modelDescriptors);

                indices = new Matrix <int>(observedDescriptors.Rows, k);
                using (Matrix <float> dist = new Matrix <float>(observedDescriptors.Rows, k))
                {
                    matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
                    mask = new Matrix <byte>(dist.Rows, 1);
                    mask.SetValue(255);
                    Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
                }

                int nonZeroCount = CvInvoke.cvCountNonZero(mask);
                if (nonZeroCount >= 4)
                {
                    nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
                    if (nonZeroCount >= 4)
                    {
                        Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 2);
                    }
                }

                if ((double)nonZeroCount / mask.Height > 0.02)
                {
                    return(true);
                }
            }

            //Draw the matched keypoints
            //var result = Features2DToolbox.DrawMatches(modelImage, modelKeyPoints, observedImage, observedKeyPoints, indices, new Bgr(0, 0, 255), new Bgr(255, 0, 0), mask, Features2DToolbox.KeypointDrawType.DEFAULT);
            //result.Save( @"C:\Users\D.Markachev\Desktop\bleh-keypoints.jpg" );

            return(false);
        }