/// <summary>
/// Filter the license plate to remove noise
/// </summary>
/// <param name="plate">The license plate image</param>
/// <returns>License plate image without the noise</returns>
private static UMat FilterPlate(UMat plate, int threshold_parameter)
{
UMat thresh = new UMat();
//Modify line height(modifica captura de linea por color de pixel)
CvInvoke.Threshold(plate, thresh, threshold_parameter, 255, ThresholdType.BinaryInv);
//Image<Gray, Byte> thresh = plate.ThresholdBinaryInv(new Gray(120), new Gray(255));
SaveImageClass.SaveImage(plate, "plate.jpg");
Size plateSize = plate.Size;
using (Mat plateMask = new Mat(plateSize.Height, plateSize.Width, DepthType.Cv8U, 1))
using (Mat plateCanny = new Mat())
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
plateMask.SetTo(new MCvScalar(255.0));
CvInvoke.Canny(plate, plateCanny, 100, 50);
CvInvoke.FindContours(plateCanny, contours, null, RetrType.External, ChainApproxMethod.ChainApproxSimple);
int count = contours.Size;
for (int i = 0; i < count; i++)
{
using (VectorOfPoint contour = contours[i])
{
Rectangle rect = CvInvoke.BoundingRectangle(contour);
if (rect.Height > (plateSize.Height >> 1))
{
rect.X -= 1; rect.Y -= 1; rect.Width += 2; rect.Height += 2;
Rectangle roi = new Rectangle(Point.Empty, plate.Size);
rect.Intersect(roi);
CvInvoke.Rectangle(plateMask, rect, new MCvScalar(), -1);
//plateMask.Draw(rect, new Gray(0.0), -1);
}
}
}
thresh.SetTo(new MCvScalar(), plateMask);
}
SaveImageClass.SaveImage(thresh, "thresh1.jpg");
CvInvoke.Erode(thresh, thresh, null, new Point(-1, -1), 1, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
SaveImageClass.SaveImage(thresh, "threshErode.jpg");
CvInvoke.Dilate(thresh, thresh, null, new Point(-1, -1), 1, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
SaveImageClass.SaveImage(thresh, "threshDilate.jpg");
return(thresh);
}
private void FindLicensePlate(
VectorOfVectorOfPoint contours, int[,] hierachy, int idx, IInputArray gray, IInputArray canny,
List <IInputOutputArray> licensePlateImagesList, List <IInputOutputArray> filteredLicensePlateImagesList, List <RotatedRect> detectedLicensePlateRegionList,
List <String> licenses, int ocr_mode, int threshold_parameter)
{
for (; idx >= 0; idx = hierachy[idx, 0])
{
int numberOfChildren = GetNumberOfChildren(hierachy, idx);
//if it does not contains any children (charactor), it is not a license plate region
if (numberOfChildren == 0)
{
continue;
}
using (VectorOfPoint contour = contours[idx])
{
if (CvInvoke.ContourArea(contour) > 400)
{
if (numberOfChildren < 6)
{
//If the contour has less than 6 children, it is not a license plate (assuming license plate has at least 3 charactor)
//However we should search the children of this contour to see if any of them is a license plate
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, threshold_parameter);
continue;
}
RotatedRect box = CvInvoke.MinAreaRect(contour);
if (box.Angle < -45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle += 90.0f;
}
else if (box.Angle > 45.0)
{
float tmp = box.Size.Width;
box.Size.Width = box.Size.Height;
box.Size.Height = tmp;
box.Angle -= 90.0f;
}
double whRatio = (double)box.Size.Width / box.Size.Height;
if (!(3.0 < whRatio && whRatio < 10.0))
//if (!(1.0 < whRatio && whRatio < 2.0))
{
//if the width height ratio is not in the specific range,it is not a license plate
//However we should search the children of this contour to see if any of them is a license plate
//Contour<Point> child = contours.VNext;
if (hierachy[idx, 2] > 0)
{
FindLicensePlate(contours, hierachy, hierachy[idx, 2], gray, canny, licensePlateImagesList,
filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, threshold_parameter);
}
continue;
}
using (UMat tmp1 = new UMat())
using (UMat tmp2 = new UMat())
{
PointF[] srcCorners = box.GetVertices();
PointF[] destCorners = new PointF[] {
new PointF(0, box.Size.Height - 1),
new PointF(0, 0),
new PointF(box.Size.Width - 1, 0),
new PointF(box.Size.Width - 1, box.Size.Height - 1)
};
using (Mat rot = CvInvoke.GetAffineTransform(srcCorners, destCorners))
{
//box.Center.X -= 20;
//box.Size.Height += 20;
//box.Size.Width += 20;
//box.Center.Y -= 20;
CvInvoke.WarpAffine(gray, tmp1, rot, Size.Round(box.Size));
}
SaveImageClass.SaveImage(gray, "gray2.jpg");
SaveImageClass.SaveImage(tmp1, "tmp1.jpg");
//resize the license plate such that the front is ~ 10-12. This size of front results in better accuracy from tesseract
Size approxSize = new Size(240, 180);
double scale = Math.Min(approxSize.Width / box.Size.Width, approxSize.Height / box.Size.Height);
Size newSize = new Size((int)Math.Round(box.Size.Width * scale), (int)Math.Round(box.Size.Height * scale));
CvInvoke.Resize(tmp1, tmp2, newSize, 0, 0, Inter.Cubic);
SaveImageClass.SaveImage(tmp1, "tmp1after.jpg");
SaveImageClass.SaveImage(tmp2, "tmp2.jpg");
//removes some pixels from the edge
int edgePixelSize = 3;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize));
UMat plate = new UMat(tmp2, newRoi);
SaveImageClass.SaveImage(plate, "plate.jpg");
UMat filteredPlate = new UMat();
filteredPlate = FilterPlate(plate, threshold_parameter);
SaveImageClass.SaveImage(filteredPlate, "filtered.jpg");
StringBuilder strBuilder = new StringBuilder();
switch (ocr_mode)
{
case 1:
{
strBuilder = TesseractOCR.GetText(filteredPlate, _ocr);
break;
}
case 2:
{
strBuilder = GoogleApiOCR.GetText(filteredPlate);
break;
}
case 3:
{
strBuilder = ComputerVisionOCR.GetText(filteredPlate);
break;
}
default:
break;
}
if (strBuilder != null)
{
licenses.Add(strBuilder.ToString());
licensePlateImagesList.Add(plate);
filteredLicensePlateImagesList.Add(filteredPlate);
detectedLicensePlateRegionList.Add(box);
}
}
}
}
}
}
/*
* /// <summary>
* /// Compute the white pixel mask for the given image.
* /// A white pixel is a pixel where: saturation < 40 AND value > 200
* /// </summary>
* /// <param name="image">The color image to find white mask from</param>
* /// <returns>The white pixel mask</returns>
* private static Image<Gray, Byte> GetWhitePixelMask(Image<Bgr, byte> image)
* {
* using (Image<Hsv, Byte> hsv = image.Convert<Hsv, Byte>())
* {
* Image<Gray, Byte>[] channels = hsv.Split();
*
* try
* {
* //channels[1] is the mask for satuation less than 40, this is the mask for either white or black pixels
* channels[1]._ThresholdBinaryInv(new Gray(40), new Gray(255));
*
* //channels[2] is the mask for bright pixels
* channels[2]._ThresholdBinary(new Gray(200), new Gray(255));
*
* CvInvoke.BitwiseAnd(channels[1], channels[2], channels[0], null);
* }
* finally
* {
* channels[1].Dispose();
* channels[2].Dispose();
* }
* return channels[0];
* }
* }*/
/// <summary>
/// Detect license plate from the given image
/// </summary>
/// <param name="img">The image to search license plate from</param>
/// <param name="licensePlateImagesList">A list of images where the detected license plate regions are stored</param>
/// <param name="filteredLicensePlateImagesList">A list of images where the detected license plate regions (with noise removed) are stored</param>
/// <param name="detectedLicensePlateRegionList">A list where the regions of license plate (defined by an MCvBox2D) are stored</param>
/// <param name="ocr_mode">Bool to check the ocr mode </param>
/// <param name="canny_thres">Canny threshold will take 3 values 20, 30, 40, 50</param>
/// <returns>The list of words for each license plate</returns>
/// <returns></returns>
public List <String> DetectLicensePlate(
IInputArray img,
List <IInputOutputArray> licensePlateImagesList,
List <IInputOutputArray> filteredLicensePlateImagesList,
List <RotatedRect> detectedLicensePlateRegionList,
int ocr_mode)
{
List <String> licenses = new List <String>();
using (Mat gray = new Mat())
using (Mat canny = new Mat())
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
CvInvoke.CvtColor(img, gray, ColorConversion.Bgr2Gray);
CvInvoke.Canny(gray, canny, 100, 50, 3, false);
int[,] hierachy = CvInvoke.FindContourTree(canny, contours, ChainApproxMethod.ChainApproxSimple);
SaveImageClass.SaveImage(gray, "gray.jpg");
SaveImageClass.SaveImage(canny, "canny.jpg");
for (int i = 0; i <= 5; i++)
{
switch (i)
{
case 0:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 80);
break;
}
case 1:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 100);
break;
}
case 2:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 120);
break;
}
case 3:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 130);
break;
}
case 4:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 150);
break;
}
case 5:
{
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses, ocr_mode, 170);
break;
}
default:
break;
}
}
}
return(licenses);
}
