static void Main(string[] args)
{
int errorCode = 0;
TextRecognizer.InitTextRecognizer();
InitParameters();
//foreach (var file in Directory.EnumerateFiles(@"D:\Imagini ANPR auto\1", "*.jpg"))
foreach (var file in Directory.EnumerateFiles(@"D:\Imagini ANPR auto\5", "2*.png"))
{
Stopwatch watch = Stopwatch.StartNew(); // time the detection process
Mat imgOriginal = new Mat(file);
Mat imgGrayScale = new Mat();
Mat imgThresh = new Mat();
List <KeyValuePair <string, bool> > licensePlateNumber = new List <KeyValuePair <string, bool> >();
ImageProcess.Preprocess(imgOriginal, ref imgGrayScale, ref imgThresh, ref errorCode);
if (Properties.Settings.Default.debug)
{
CvInvoke.Imshow("Original image", imgOriginal);
CvInvoke.Imshow("Threshold", imgThresh);
}
List <KeyValuePair <Mat, Mat> > licensePlates = PlateExtraction.DetectPlate(imgGrayScale, imgThresh, ref errorCode);
foreach (var licensePlate in licensePlates)
{
if (licensePlate.Value != null)
{
licensePlateNumber.Add(TextRecognizer.RecognizeText(licensePlate.Value));
}
}
foreach (KeyValuePair <string, bool> pair in licensePlateNumber)
{
if (pair.Value == true)
{
Console.WriteLine("License plate # " + pair.Key);
break;
}
else
{
Console.WriteLine("License plate # " + LicensePlateRegex.LicensePlateNumberProcess(pair.Key));
}
}
watch.Stop(); //stop the timer
Console.WriteLine(watch.Elapsed);
CvInvoke.WaitKey();
CvInvoke.DestroyAllWindows();
}
Console.ReadLine();
}
/// <summary>
///
/// </summary>
/// <param name="potentialPlates">List of potentials plates</param>
/// <param name="pass">What pass is executing</param>
/// <param name="errorCode">Error code</param>
/// <returns>Key value pair of license plate image and its treshold</returns>
private static KeyValuePair <Mat, Mat> FindPlateInPotentialPlates(List <Mat> potentialPlates, string pass, ref int errorCode)
{
// Initiate license plate variable
KeyValuePair <Mat, Mat> licensePlate = new KeyValuePair <Mat, Mat>();
// Initiate variable for if license plate was found
bool licensePlateFound = false;
try
{
// Check what pass
if (pass == "firstPass")
{
// Loop through all potential plates
foreach (var potentialPlate in potentialPlates)
{
// Initate images used
Mat imgBilateralFilter = new Mat();
Mat imgThresh = new Mat();
Mat imgOpen = new Mat();
// Initiate structuring elements used in morphological procedures
Mat structuringElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(150, 150), new Point(-1, -1));
Mat openElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(7, 7), new Point(-1, -1));
Mat closeElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(8, 15), new Point(-1, -1));
Mat erodeElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(3, 3), new Point(-1, -1));
// Initiate other variables
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
List <Rectangle> boundingRectangles = new List <Rectangle>();
// Maximize contrast of a potential plate
Mat imgMaxContrast = ImageProcess.MaximizeContrast(potentialPlate, ref errorCode);
// Apply bilateral filter to image with contrast maximized
CvInvoke.BilateralFilter(imgMaxContrast, imgBilateralFilter, 5, 20, 20); // 40 20 20
// Do morphological operation of tophat
CvInvoke.MorphologyEx(imgBilateralFilter, imgOpen, MorphOp.Tophat, structuringElement, new Point(-1, -1), 2, BorderType.Default, new MCvScalar());
// Do adaptive treshold to tophat image
CvInvoke.AdaptiveThreshold(imgOpen, imgThresh, 255, AdaptiveThresholdType.GaussianC, ThresholdType.BinaryInv, 295, 19); // first pass
// Do morphological operation of open to thresholded image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Open, openElement, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
// Do morphological operation of erode to open image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Erode, erodeElement, new Point(-1, -1), 1, BorderType.Constant, new MCvScalar());
// Do morphological operation of close to thresholded image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Close, closeElement, new Point(-1, -1), 1, BorderType.Constant, new MCvScalar());
// Find contours in erode image
CvInvoke.FindContours(imgThresh, contours, null, RetrType.External, ChainApproxMethod.ChainApproxSimple);
Image <Bgr, byte> imgContours = imgThresh.ToImage <Bgr, byte>();
// Loop through found contours
for (int i = 0; i < contours.Size; i++)
{
// Create a bounding rectangle of the contour
var boundingRectangle = CvInvoke.BoundingRectangle(contours[i]);
// Check if contour has required dimensions
if (boundingRectangle.Height >= Properties.Settings.Default.boundingRectangleHeightMin && boundingRectangle.Height <= Properties.Settings.Default.boundingRectangleHeightMax && boundingRectangle.Width <= Properties.Settings.Default.boundingRectangleWidthMax)
{
CvInvoke.Rectangle(imgContours, boundingRectangle, new MCvScalar(0, 0, 255));
// Add bounding rectangle to the list of bounding rectangles
boundingRectangles.Add(boundingRectangle);
}
}
// Check if the list of bounding rectangles has the required number of items
if (boundingRectangles.Count >= 5 && boundingRectangles.Count <= 9)
{
// Make a key value pair with the cropped image and its threshold
licensePlate = new KeyValuePair <Mat, Mat>(potentialPlate, imgThresh);
licensePlateFound = true;
// Check if debug enabled
if (Properties.Settings.Default.debug)
{
// Show image of plate segmented
CvInvoke.Imshow("Plate segmented first pass", imgContours.Mat);
//CvInvoke.Imshow("Plate segmented first pass", potentialPlate);
}
// Stop from searching further
break;
}
}
}
else if (pass == "secondPass")
{
foreach (var potentialPlate in potentialPlates)
{
// Initate images used
Mat imgBilateralFilter = new Mat();
Mat imgThresh = new Mat();
Mat imgOpen = new Mat();
// Initiate structuring elements used in morphological procedures
Mat structuringElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(150, 150), new Point(-1, -1));
Mat openElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(7, 7), new Point(-1, -1));
Mat closeElement = CvInvoke.GetStructuringElement(ElementShape.Rectangle, new Size(5, 5), new Point(-1, -1));
Mat erodeElement = CvInvoke.GetStructuringElement(ElementShape.Ellipse, new Size(3, 3), new Point(-1, -1));
// Initiate other variables
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
List <Rectangle> boundingRectangles = new List <Rectangle>();
// Maximize contrast of a potential plate
Mat imgMaxContrast = ImageProcess.MaximizeContrast(potentialPlate, ref errorCode);
// Apply bilateral filter to image with contrast maximized
CvInvoke.BilateralFilter(imgMaxContrast, imgBilateralFilter, 5, 10, 10); // 20 10 10
// Do morphological operation of tophat
CvInvoke.MorphologyEx(imgBilateralFilter, imgOpen, MorphOp.Tophat, structuringElement, new Point(-1, -1), 1, BorderType.Default, new MCvScalar());
// Do adaptive treshold to tophat image
CvInvoke.AdaptiveThreshold(imgOpen, imgThresh, 255, AdaptiveThresholdType.GaussianC, ThresholdType.BinaryInv, 105, 5); // second pass
// Do morphological operation of open to thresholded image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Open, openElement, new Point(-1, -1), 1, BorderType.Constant, new MCvScalar());
// Do morphological operation of erode to open image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Erode, erodeElement, new Point(-1, -1), 1, BorderType.Constant, new MCvScalar());
// Do morphological operation of close to thresholded image
CvInvoke.MorphologyEx(imgThresh, imgThresh, MorphOp.Close, closeElement, new Point(-1, -1), 1, BorderType.Constant, new MCvScalar());
// Find contours in erode image
CvInvoke.FindContours(imgThresh, contours, null, RetrType.External, ChainApproxMethod.ChainApproxSimple);
Image <Bgr, byte> imgContours = imgThresh.ToImage <Bgr, byte>();
// Loop through found contours
for (int i = 0; i < contours.Size; i++)
{
// Create a bounding rectangle of the contour
var boundingRectangle = CvInvoke.BoundingRectangle(contours[i]);
// Check if contour has required dimensions
if (boundingRectangle.Height >= Properties.Settings.Default.boundingRectangleHeightMin && boundingRectangle.Height <= Properties.Settings.Default.boundingRectangleHeightMax)
{
CvInvoke.Rectangle(imgContours, boundingRectangle, new MCvScalar(0, 0, 255));
// Add bounding rectangle to the list of bounding rectangles
boundingRectangles.Add(boundingRectangle);
}
}
// Check if the list of bounding rectangles has the required number of items
if (boundingRectangles.Count >= 5 && boundingRectangles.Count <= 9)
{
// Make a key value pair with the cropped image and its threshold
licensePlate = new KeyValuePair <Mat, Mat>(potentialPlate, imgThresh);
licensePlateFound = true;
// Check if debug enabled
if (Properties.Settings.Default.debug)
{
// Show image of plate segmented
CvInvoke.Imshow("Plate segmented second pass", imgContours.Mat);
//CvInvoke.Imshow("Plate segmented second pass", potentialPlate);
}
// Stop from searching further
break;
}
}
}
// Check if license plate has been found
if (!licensePlateFound)
{
// Return null
return(new KeyValuePair <Mat, Mat>());
}
else
{
// Return the key value pair
return(licensePlate);
}
}
catch (Exception ex)
{
Console.WriteLine(ex);
errorCode = 8;
return(new KeyValuePair <Mat, Mat>());
}
}
