Come dicevo Opencv ha dei wraPPER per altri linguaggi come il c++.
Due si chiamano Emgucv e Aforge.
using System;
using System.Collections.Generic;
using System.Text;
using System.Drawing;
using Emgu.Util;
using Emgu.CV;
using Emgu.CV.Structure;
using tessnet2;
using System.Diagnostics;
namespace LicensePlateRecognition
{
/// <summary>
/// A license plate detector
/// </summary>
public class LicensePlateDetector : DisposableObject
{
private Tesseract _ocr;
/// <summary>
/// Create a license plate detector
/// </summary>
public LicensePlateDetector()
{
//create OCR
_ocr = new Tesseract();
//You can download more language definition data from
//http://code.google.com/p/tesseract-ocr/downloads/list
//Languages supported includes:
//Dutch, Spanish, German, Italian, French and English
_ocr.Init("eng", false);
}
/// <summary>
/// Detect license plate from the given image
/// </summary>
/// <param name="img">The image to search license plate from</param>
/// <param name="licensePlateList">A list of images where the detected license plate region is stored</param>
/// <param name="filteredLicensePlateList">A list of images where the detected license plate region with noise removed is stored</param>
/// <param name="boxList">A list where the region of license plate, defined by an MCvBox2D is stored</param>
/// <returns>The list of words for each license plate</returns>
public List<List<Word>> DetectLicensePlate(Image<Bgr, byte> img, List<Image<Gray, Byte>> licensePlateList, List<Image<Gray, Byte>> filteredLicensePlateList, List<MCvBox2D> boxList)
{
//Stopwatch w = Stopwatch.StartNew();
List<List<Word>> licenses = new List<List<Word>>();
using (Image<Gray, byte> gray = img.Convert<Gray, Byte>())
using (Image<Gray, Byte> canny = new Image<Gray, byte>(gray.Size))
using (MemStorage stor = new MemStorage())
{
CvInvoke.cvCanny(gray, canny, 100, 50, 3);
Contour<Point> contours = canny.FindContours(
Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_TREE,
stor);
FindLicensePlate(contours, gray, canny, licensePlateList, filteredLicensePlateList, boxList, licenses);
}
//w.Stop();
return licenses;
}
private void FindLicensePlate(
Contour<Point> contours, Image<Gray, Byte> gray, Image<Gray, Byte> canny,
List<Image<Gray, Byte>> licensePlateList, List<Image<Gray, Byte>> filteredLicensePlateList, List<MCvBox2D> boxList,
List<List<Word>> licenses)
{
for (; contours != null; contours = contours.HNext)
{
Contour<Point> approxContour = contours.ApproxPoly(contours.Perimeter * 0.05, contours.Storage);
if (approxContour.Area > 100 && approxContour.Total == 4)
{
//img.Draw(contours, new Bgr(Color.Red), 1);
if (!IsParallelogram(approxContour.ToArray()))
{
Contour<Point> child = contours.VNext;
if (child != null)
FindLicensePlate(child, gray, canny, licensePlateList, filteredLicensePlateList, boxList, licenses);
continue;
}
MCvBox2D box = approxContour.GetMinAreaRect();
double whRatio = (double)box.size.Width / box.size.Height;
if (!(3.0 < whRatio && whRatio < 8.0))
{
Contour<Point> child = contours.VNext;
if (child != null)
FindLicensePlate(child, gray, canny, licensePlateList, filteredLicensePlateList, boxList, licenses);
continue;
}
Image<Gray, Byte> plate = gray.Copy(box);
Image<Gray, Byte> filteredPlate = FilterPlate(plate);
List<Word> words;
using (Bitmap bmp = filteredPlate.Bitmap)
words = _ocr.DoOCR(bmp, filteredPlate.ROI);
licenses.Add(words);
licensePlateList.Add(plate);
filteredLicensePlateList.Add(filteredPlate);
boxList.Add(box);
}
}
}
/// <summary>
/// Check if the four points forms a parallelogram
/// </summary>
/// <param name="pts">The four points that defines a polygon</param>
/// <returns>True if the four points defines a parallelogram</returns>
private static bool IsParallelogram(Point[] pts)
{
LineSegment2D[] edges = PointCollection.PolyLine(pts, true);
double diff1 = Math.Abs(edges[0].Length - edges[2].Length);
double diff2 = Math.Abs(edges[1].Length - edges[3].Length);
if (diff1 / edges[0].Length <= 0.05 && diff1 / edges[2].Length <= 0.05
&& diff2 / edges[1].Length <= 0.05 && diff2 / edges[3].Length <= 0.05)
{
return true;
}
return false;
}
/// <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 Image<Gray, Byte> FilterPlate(Image<Gray, Byte> plate)
{
Image<Gray, Byte> thresh = plate.ThresholdBinaryInv(new Gray(120), new Gray(255));
using (Image<Gray, Byte> plateMask = new Image<Gray, byte>(plate.Size))
using (Image<Gray, Byte> plateCanny = plate.Canny(new Gray(100), new Gray(50)))
using (MemStorage stor = new MemStorage())
{
plateMask.SetValue(255.0);
for (
Contour<Point> contours = plateCanny.FindContours(
Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_EXTERNAL,
stor);
contours != null; contours = contours.HNext)
{
Rectangle rect = contours.BoundingRectangle;
if (rect.Height > (plate.Height >> 1))
{
rect.X -= 1; rect.Y -= 1; rect.Width += 2; rect.Height += 2;
rect.Intersect(plate.ROI);
plateMask.Draw(rect, new Gray(0.0), -1);
}
}
thresh.SetValue(0, plateMask);
}
thresh._Erode(1);
thresh._Dilate(1);
return thresh;
}
protected override void DisposeObject()
{
_ocr.Dispose();
}
}
}
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