public CornerDetect()
{
int cornerCount = 150;
using (IplImage dstImg1 = new IplImage(FilePath.Image.Lenna, LoadMode.AnyColor | LoadMode.AnyDepth))
using (IplImage dstImg2 = dstImg1.Clone())
using (IplImage srcImgGray = new IplImage(FilePath.Image.Lenna, LoadMode.GrayScale))
using (IplImage eigImg = new IplImage(srcImgGray.GetSize(), BitDepth.F32, 1))
using (IplImage tempImg = new IplImage(srcImgGray.GetSize(), BitDepth.F32, 1))
{
CvPoint2D32f[] corners;
Cv.GoodFeaturesToTrack(srcImgGray, eigImg, tempImg, out corners, ref cornerCount, 0.1, 15);
Cv.FindCornerSubPix(srcImgGray, corners, cornerCount, new CvSize(3, 3), new CvSize(-1, -1), new CvTermCriteria(20, 0.03));
for (int i = 0; i < cornerCount; i++)
{
Cv.Circle(dstImg1, corners[i], 3, new CvColor(255, 0, 0), 2);
}
cornerCount = 150;
Cv.GoodFeaturesToTrack(srcImgGray, eigImg, tempImg, out corners, ref cornerCount, 0.1, 15, null, 3, true, 0.01);
Cv.FindCornerSubPix(srcImgGray, corners, cornerCount, new CvSize(3, 3), new CvSize(-1, -1), new CvTermCriteria(20, 0.03));
for (int i = 0; i < cornerCount; i++)
{
Cv.Circle(dstImg2, corners[i], 3, new CvColor(0, 0, 255), 2);
}
using (new CvWindow("EigenVal", WindowMode.AutoSize, dstImg1))
using (new CvWindow("Harris", WindowMode.AutoSize, dstImg2))
{
Cv.WaitKey(0);
}
}
}
public IplImage PreProcess(IplImage image)
{
double min, max;
Cv.MinMaxLoc(image, out min, out max);
image.GetSize()
}
//src_img:入出力
public static void Median8(IplImage src_img)
{
IplImage dst_img = Cv.CreateImage(src_img.GetSize(), BitDepth.U8, 1);
Median8(src_img, dst_img);
Cv.Copy(dst_img, src_img);//dst_img->src_img
Cv.ReleaseImage(dst_img);
}
/// <summary>
/// 指定されたPictureBoxに画像を描画する
/// </summary>
/// <param name="pb">描画先のPictureBox</param>
/// <param name="img">描画する画像</param>
private void drawPicture(OpenCvSharp.UserInterface.PictureBoxIpl pb, IplImage img)
{
using (IplImage pictureImage = new IplImage(img.GetSize(), img.Depth, img.NChannels))
{
pictureImage.SetROI(0, 0, pb.Width, pb.Height);
img.Resize(pictureImage);
pb.ImageIpl = pictureImage;
}
}
public CornerDetect()
{
// cvGoodFeaturesToTrack, cvFindCornerSubPix
// 画像中のコーナー（特徴点）検出
int cornerCount = 150;
using (IplImage dstImg1 = new IplImage(Const.ImageLenna, LoadMode.AnyColor | LoadMode.AnyDepth))
using (IplImage dstImg2 = dstImg1.Clone())
using (IplImage srcImgGray = new IplImage(Const.ImageLenna, LoadMode.GrayScale))
using (IplImage eigImg = new IplImage(srcImgGray.GetSize(), BitDepth.F32, 1))
using (IplImage tempImg = new IplImage(srcImgGray.GetSize(), BitDepth.F32, 1))
{
CvPoint2D32f[] corners;
// (1)cvCornerMinEigenValを利用したコーナー検出
Cv.GoodFeaturesToTrack(srcImgGray, eigImg, tempImg, out corners, ref cornerCount, 0.1, 15);
Cv.FindCornerSubPix(srcImgGray, corners, cornerCount, new CvSize(3, 3), new CvSize(-1, -1), new CvTermCriteria(20, 0.03));
// (2)コーナーの描画
for (int i = 0; i < cornerCount; i++)
{
Cv.Circle(dstImg1, corners[i], 3, new CvColor(255, 0, 0), 2);
}
// (3)cvCornerHarrisを利用したコーナー検出
cornerCount = 150;
Cv.GoodFeaturesToTrack(srcImgGray, eigImg, tempImg, out corners, ref cornerCount, 0.1, 15, null, 3, true, 0.01);
Cv.FindCornerSubPix(srcImgGray, corners, cornerCount, new CvSize(3, 3), new CvSize(-1, -1), new CvTermCriteria(20, 0.03));
// (4)コーナーの描画
for (int i = 0; i < cornerCount; i++)
{
Cv.Circle(dstImg2, corners[i], 3, new CvColor(0, 0, 255), 2);
}
// (5)画像の表示
using (new CvWindow("EigenVal", WindowMode.AutoSize, dstImg1))
using (new CvWindow("Harris", WindowMode.AutoSize, dstImg2))
{
Cv.WaitKey(0);
}
}
}
/*
* Convert OpenCvImage into 2D byte array
*/
public static byte[,] IplImageToMatlabImage(IplImage image)
{
int h = image.GetSize().Height;
int w = image.GetSize().Width;
//Set size and colour mode, to grayscale, use unsigned 8 bit, one channel
IplImage gray = new IplImage(new CvSize(w, h), BitDepth.U8, 1);
Cv.CvtColor(image, gray, ColorConversion.BgrToGray);
byte[,] array = new byte[h, w];
for (int i = 0; i < h - 1; i++)
{
for (int j = 0; j < w - 1; j++)
{
double value = gray.GetReal2D(i, j);
array[i, j] = Convert.ToByte(value);
}
}
return(array);
}
//src_img:入出力
public static bool ApplyMask(int[] Mask, IplImage src_img)
{
if ((Mask.Length != Const.Neighborhood8) && (Mask.Length != Const.Neighborhood4))
{
return(false);
}
IplImage dst_img = Cv.CreateImage(src_img.GetSize(), BitDepth.U8, 1);
ApplyMask(Mask, src_img, dst_img);
Cv.Copy(dst_img, src_img);//dst_img->src_img
Cv.ReleaseImage(dst_img);
return(true);
}
}/* */
//src_img:入出力
public static bool FastestMedian(IplImage src_img, int n)
{
if ((n & 1) == 0)
{
return(false); //偶数はさいなら
}
IplImage dst_img = Cv.CreateImage(src_img.GetSize(), BitDepth.U8, 1);
FastestMedian(src_img, dst_img, n);
Cv.Copy(dst_img, src_img);//dst_img->src_img
Cv.ReleaseImage(dst_img);
return(true);
}
/// <summary>
/// フルカラー画像(24bit)をグレースケール画像(8bit)に変換する
/// mImageFull --> mImageGray
/// </summary>
private void convertFullToGray()
{
mImageGray = new IplImage(mImageFull.GetSize(), BitDepth.U8, 1);
mImageFull.CvtColor(mImageGray, ColorConversion.BgrToGray);
}
public static string[] Recognize(IplImage input, TextDetectionParams _params, Chain[] chains, List <Tuple <Point2d, Point2d> > compBB, List <Tuple <CvPoint, CvPoint> > chainBB, DigitsRecognitionMethod digitsRecognition)
{
List <string> variants = new List <string>();
//convert to grayscale
IplImage grayImage = Cv.CreateImage(input.GetSize(), BitDepth.U8, 1);
Cv.CvtColor(input, grayImage, ColorConversion.RgbToGray);
for (int i = 0; i < chainBB.Count; i++)
{
Rect chainRect = new Rect(chainBB[i].Item1.X, chainBB[i].Item1.Y, chainBB[i].Item2.X - chainBB[i].Item1.X, chainBB[i].Item2.Y - chainBB[i].Item1.Y);
CvPoint center = new CvPoint((chainBB[i].Item1.X + chainBB[i].Item2.X) / 2, (chainBB[i].Item1.Y + chainBB[i].Item2.Y) / 2);
//work out if total width of chain is large enough
if (chainBB[i].Item2.X - chainBB[i].Item1.X < input.Width / _params.MaxImgWidthToTextRatio)
{
continue;
}
//eliminate chains with components of lower height than required minimum
int minHeight = chainBB[i].Item2.Y - chainBB[i].Item1.Y;
for (int j = 0; j < chains[i].components.Count; j++)
{
minHeight = Math.Min(minHeight, compBB[chains[i].components[j]].Item2.y - compBB[chains[i].components[j]].Item1.y);
}
if (minHeight < _params.MinCharacterHeight)
{
continue;
}
//invert direction if angle is in 3rd/4th quadrants
if (chains[i].direction.x < 0)
{
chains[i].direction.x = -chains[i].direction.x;
chains[i].direction.y = -chains[i].direction.y;
}
//work out chain angle
double theta_deg = 180 * Math.Atan2(chains[i].direction.y, chains[i].direction.x) / Math.PI;
if (Math.Abs(theta_deg) > _params.MaxAngle)
{
continue;
}
if ((chainBB.Count == 2) && (Math.Abs(theta_deg) > 5))
{
continue;
}
//Console.WriteLine("Chain #" + i + " angle: " + theta_deg + " degress");
//create copy of input image including only the selected components
Mat inputMat = new Mat(input);
Mat grayMat = new Mat(grayImage);
Mat componentsImg = Mat.Zeros(new Size(grayMat.Cols, grayMat.Rows), grayMat.Type());
//CvMat componentsImg = _componentsImg.ToCvMat();
Mat componentsImgRoi = null;
List <CvPoint> compCoords = new List <CvPoint>();
chains[i].components = chains[i].components.Distinct().ToList();
int order = 0;
//ordering components bounding boxes by x coord
var ordCompBB = compBB.OrderBy(x => x.Item1.x).ToList();
List <string> digits = new List <string>();
for (int j = 0; j < ordCompBB.Count; j++)
{
Rect roi = new Rect(ordCompBB[j].Item1.x, ordCompBB[j].Item1.y, ordCompBB[j].Item2.x - ordCompBB[j].Item1.x, ordCompBB[j].Item2.y - ordCompBB[j].Item1.y);
if (!chainRect.Contains(roi))
{
continue;
}
Mat componentRoi = new Mat(grayMat, roi);
compCoords.Add(new CvPoint(ordCompBB[j].Item1.x, ordCompBB[j].Item1.y));
compCoords.Add(new CvPoint(ordCompBB[j].Item2.x, ordCompBB[j].Item2.y));
compCoords.Add(new CvPoint(ordCompBB[j].Item1.x, ordCompBB[j].Item2.y));
compCoords.Add(new CvPoint(ordCompBB[j].Item2.x, ordCompBB[j].Item1.y));
Mat thresholded = new Mat(grayMat, roi);
Cv2.Threshold(componentRoi, thresholded, 0, 255, ThresholdType.Otsu | ThresholdType.BinaryInv);
componentsImgRoi = new Mat(componentsImg, roi);
Cv2.Threshold(componentRoi, componentsImgRoi, 0, 255, ThresholdType.Otsu | ThresholdType.BinaryInv);
//var size = thresholded.Size();
//digits.Add(new Bitmap(size.Width, size.Height, (int)thresholded.Step1(), System.Drawing.Imaging.PixelFormat.Format24bppRgb, thresholded.Data));
if (digitsRecognition == DigitsRecognitionMethod.Neural || digitsRecognition == DigitsRecognitionMethod.Both)
{
string file = FileManager.TempBitmap;
Cv2.ImWrite(file, thresholded);
try
{
digits.Add(file);
}
catch
{
GC.Collect();
GC.WaitForFullGCComplete();
}
//digits.Last().Save("test" + order + ".bmp");
order++;
}
//else if (digitsRecognition == DigitsRecognitionMethod.Tesseract || digitsRecognition == DigitsRecognitionMethod.Both)
//{
// DO NOTHING
//}
}
if (digitsRecognition == DigitsRecognitionMethod.Neural || digitsRecognition == DigitsRecognitionMethod.Both)
{
//TODO: neural recognition
var result = OCRParser.ParseNeural(digits.ToArray());
variants.Add(result.Value);
//variants.AddRange(OCRParser.ParseNeural(digits.ToArray()));
//variants.Add(BibOCR.OCRParser.ParseBib(digits.ToArray()));
}
if (digitsRecognition == DigitsRecognitionMethod.Tesseract || digitsRecognition == DigitsRecognitionMethod.Both)
{
CvRect _roi = GetBoundingBox(compCoords, new CvSize(input.Width, input.Height));
//ROI area can be null if outside of clipping area
if ((_roi.Width == 0) || (_roi.Height == 0))
{
continue;
}
//rotate each component coordinates
const int border = 3;
Mat _mat = new Mat(_roi.Height + 2 * border, _roi.Width + 2 * border, grayMat.Type());
Mat tmp = new Mat(grayMat, _roi);
//copy bounded box from rotated mat to new mat with borders - borders are needed to improve OCR success rate
Mat mat = new Mat(_mat, new Rect(border, border, _roi.Width, _roi.Height));
tmp.CopyTo(mat);
//resize image to improve OCR success rate
float upscale = 5.0f;
Cv2.Resize(mat, mat, new Size(0, 0), upscale, upscale);
//erode text to get rid of thin joints
int s = (int)(0.05 * mat.Rows); // 5% of up-scaled size
Mat elem = Cv2.GetStructuringElement(StructuringElementShape.Ellipse, new Size(2 * s + 1, 2 * s + 1), new Point(s, s));
//Cv2.Erode(mat, mat, elem);
//Cv2.Threshold(mat, mat, 0, 255, ThresholdType.Otsu | ThresholdType.BinaryInv);
string file = FileManager.TempPng;
Cv2.ImWrite(file, mat);
// TODO: Pass it to Tesseract API
variants.Add(OCRParser.ParseTesseract(file));
}
//for (int j = 0; j < digits.Count; j++)
// digits[j].Dispose();
digits.Clear();
GC.Collect();
GC.WaitForFullGCComplete(5000);
}
Cv.ReleaseImage(grayImage);
return(variants.Distinct().ToArray());
}
