private ImageFeature <float>[] SIFFt(Bitmap M)
{
Image <Gray, byte> image = new Image <Gray, byte>(M);
SIFTDetector sift = new SIFTDetector();
VectorOfKeyPoint keys = new VectorOfKeyPoint();
MKeyPoint[] key = sift.DetectKeyPoints(image, null);
ImageFeature <float>[] res = sift.ComputeDescriptors(image, null, key);
return(res);
}
//public static string DoImageRegonition(string FullFeaFName, Stream ImgStream)
public static Dictionary <string, string> DoImageRegonition(string[] SevenFeas, string[] CocaFeas, Stream ImgStream)
{
Dictionary <string, string> regres = new Dictionary <string, string>(4);
StringBuilder sb = new StringBuilder();
const int Seven_DV = 400;
const int Coca_DV = 300;
try
{
SIFTDetector siftdector = new SIFTDetector();
//the following code is unnecessary because we will extract the feature first.
// this other way this image is pre-transformed to gray-scale.
//the following codes are needed to be refactory
// Image<Gray, Byte> modelImage = new Image<Gray, byte>(FullMoldeImg);
//Image<Gray, Byte> modelImage = new Image<Gray, byte>(FullMoldeImgName);
BinaryFormatter _bf = new BinaryFormatter();
int sevenlen = SevenFeas.Length;
int cocalen = CocaFeas.Length;
//initial the dictionary variable
regres.Add("seven", "no");
regres.Add("coca", "no");
regres.Add("ma", "none");
regres.Add("excep", "none");
//Initialize the image that to be comparased
Image <Gray, Byte> observedImage = GetCVImage(ImgStream);
MKeyPoint[] objmkps = siftdector.DetectKeyPoints(observedImage);
ImageFeature[] imageFeatures = siftdector.ComputeDescriptors(observedImage, objmkps);
//PointF[] _obimgPA = GetPointFfromFeatures(imageFeatures, imageFeatures.Length);
//int _obimgPN = _obimgPA.Length;
//Doing seven matching
for (int idx = 0; idx < sevenlen; idx++)
{
//Get the feature file
Stream stream = File.Open(SevenFeas[idx], FileMode.Open);
//Deserilizing the file to get the feature
ImageFeature[] sevenFeatures = (ImageFeature[])_bf.Deserialize(stream);
stream.Dispose();
int slen = sevenFeatures.Length;
//PointF[] sevenPA = GetPointFfromFeatures(sevenFeatures, _obimgPN);
//set up the tractor
Features2DTracker seventrac = new Features2DTracker(sevenFeatures);
////Doing seven matching
Features2DTracker.MatchedImageFeature[] sevenmatchedfea = seventrac.MatchFeature(imageFeatures, 2, 20);
sevenmatchedfea = Features2DTracker.VoteForUniqueness(sevenmatchedfea, 0.8);
sevenmatchedfea = Features2DTracker.VoteForSizeAndOrientation(sevenmatchedfea, 1.5, 20);
//Get matching result matrix
HomographyMatrix sevenhomography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(sevenmatchedfea);
//Matrix<float> sevenhomography = CameraCalibration.FindHomography(sevenPA,_obimgPA,HOMOGRAPHY_METHOD.RANSAC,3).Convert<float>();
//sevenmatchedfea.
//fill result into dictionary variable
if (sevenhomography != null)
{
if (Math.Abs(sevenhomography.Sum) > Seven_DV)
{
regres["seven"] = "yes";
}
sb.Append("ssum:");
sb.Append(sevenhomography.Sum.ToString());
//sb.Append("| sidx:");
// sb.Append(idx.ToString());
break;
}
}
//Doing Coca image matching
for (int idx2 = 0; idx2 < cocalen; idx2++)
{
//Get the feature file
Stream stream = File.Open(CocaFeas[idx2], FileMode.Open);
//Deserilizing the file to get the feature
ImageFeature[] cocaFeatures = (ImageFeature[])_bf.Deserialize(stream);
stream.Dispose();
//PointF[] cocaPA = GetPointFfromFeatures(cocaFeatures, _obimgPN);
//cocaFeatures.CopyTo(cocaPA, 0);
//Matrix<float> cocahomography = CameraCalibration.FindHomography(cocaPA, _obimgPA, HOMOGRAPHY_METHOD.RANSAC, 3).Convert<float>();
//set up the tractor
Features2DTracker cocatrac = new Features2DTracker(cocaFeatures);
////Doing seven matching
Features2DTracker.MatchedImageFeature[] cocamatchedfea = cocatrac.MatchFeature(imageFeatures, 2, 20);
cocamatchedfea = Features2DTracker.VoteForUniqueness(cocamatchedfea, 0.8);
cocamatchedfea = Features2DTracker.VoteForSizeAndOrientation(cocamatchedfea, 1.5, 20);
//Get matching result matrix
HomographyMatrix cocahomography = Features2DTracker.GetHomographyMatrixFromMatchedFeatures(cocamatchedfea);
//fill result into dictionary variable
if (cocahomography != null)
{
if (Math.Abs(cocahomography.Sum) > Coca_DV)
{
regres["coca"] = "yes";
}
sb.Append("#csum:");
sb.Append(cocahomography.Sum.ToString());
//sb.Append(",cidx:");
//sb.Append(idx2.ToString());
break;
}
}
}
catch (Exception err)
{
regres["excep"] = err.Message;
Console.WriteLine(err.Message);
}
if (sb.Length > 0)
{
regres["ma"] = sb.ToString();
sb = null;
}
return(regres);
}
