【高分求解】如何用EmguCV的Surf算法？

gqqnb 2013-01-17 08:19:44

文末的代码是EmguCV里用surf算法的示例。看起来indices保存了匹配信息。因为

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);

就把两幅图画了出来，标上了特征点，而且在匹配的特征点间画上连线。如图，白色的圈就是找到的特征点，有两对特征点相匹配。

请问，除了把特征点匹配用Features2DToolbox.DrawMatches话出来以外，怎么用代码显示有多少匹配，谁匹配谁。谢谢！

       /// <summary>

        /// Draw the model image and observed image, the matched features and homography projection.

        /// </summary>

        /// <param name="modelImageFileName">The model image</param>

        /// <param name="observedImageFileName">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(String modelImageFileName, String observedImageFileName, out long matchTime)

        {

            Image<Gray, Byte> modelImage = new Image<Gray, byte>(modelImageFileName);

            Image<Gray, Byte> observedImage = new Image<Gray, byte>(observedImageFileName);

            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;

           

                //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);

                if (observedKeyPoints.Size == 0)

                    throw new Exception();



                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;

        }