1. 定义车牌识别器：
2. 使用Tesseract作为ocr引擎
3. 识别
4. 噪音处理
车牌识别类：
/// <summary>
/// A simple license plate detector
/// </summary>
public class LicensePlateDetector : DisposableObject
{
/// <summary>
/// The OCR engine
/// </summary>
private Tesseract _ocr;
/// <summary>
/// Create a license plate detector
/// </summary>
/// <param name="dataPath">
/// The datapath must be the name of the parent directory of tessdata and
/// must end in / . Any name after the last / will be stripped.
/// </param>
public LicensePlateDetector(String dataPath)
{
//create OCR engine
_ocr = new Tesseract(dataPath, "eng", OcrEngineMode.TesseractCubeCombined);
_ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
}
/// <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>
/// <returns>The list of words for each license plate</returns>
public List<String> DetectLicensePlate(
IInputArray img,
List<IInputOutputArray> licensePlateImagesList,
List<IInputOutputArray> filteredLicensePlateImagesList,
List<RotatedRect> detectedLicensePlateRegionList)
{
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);
FindLicensePlate(contours, hierachy, 0, gray, canny, licensePlateImagesList, filteredLicensePlateImagesList, detectedLicensePlateRegionList, licenses);
}
return licenses;
}
private static int GetNumberOfChildren(int[,] hierachy, int idx)
{
//first child
idx = hierachy[idx,2];
if (idx < 0)
return 0;
int count = 1;
while (hierachy[idx,0] > 0)
{
count++;
idx = hierachy[idx,0];
}
return count;
}
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)
{
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 < 3)
{
//If the contour has less than 3 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);
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);
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))
{
CvInvoke.WarpAffine(gray, tmp1, rot, Size.Round(box.Size));
}
//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);
//removes some pixels from the edge
int edgePixelSize = 2;
Rectangle newRoi = new Rectangle(new Point(edgePixelSize, edgePixelSize),
tmp2.Size - new Size(2*edgePixelSize, 2*edgePixelSize));
UMat plate = new UMat(tmp2, newRoi);
UMat filteredPlate = FilterPlate(plate);
Tesseract.Character[] words;
StringBuilder strBuilder = new StringBuilder();
using (UMat tmp = filteredPlate.Clone())
{
_ocr.Recognize(tmp);
words = _ocr.GetCharacters();
if (words.Length == 0) continue;
for (int i = 0; i < words.Length; i++)
{
strBuilder.Append(words[i].Text);
}
}
licenses.Add(strBuilder.ToString());
licensePlateImagesList.Add(plate);
filteredLicensePlateImagesList.Add(filteredPlate);
detectedLicensePlateRegionList.Add(box);
}
}
}
}
}
/// <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)
{
UMat thresh = new UMat();
CvInvoke.Threshold(plate, thresh, 120, 255, ThresholdType.BinaryInv);
//Image<Gray, Byte> thresh = plate.ThresholdBinaryInv(new Gray(120), new Gray(255));
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 = 1; 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);
}
CvInvoke.Erode(thresh, thresh, null, new Point(-1, -1), 1, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
CvInvoke.Dilate(thresh, thresh, null, new Point(-1, -1), 1, BorderType.Constant, CvInvoke.MorphologyDefaultBorderValue);
return thresh;
}
protected override void DisposeObject()
{
_ocr.Dispose();
}
}5. 调用：
...
private LicensePlateDetector _licensePlateDetector;
private Capture _capture;
private const string tessPath = @"C:\Craft\OpenCV\EmguTest\EmguCVLPR\tessdata";
private Timer _timer;
public Form1()
{
InitializeComponent();
_licensePlateDetector = new LicensePlateDetector(tessPath);
_capture = new Capture();
Detecting();
}
public void Detecting()
{
var openFileDialog1 = new OpenFileDialog();
DialogResult result = openFileDialog1.ShowDialog();
if (result == DialogResult.OK)
{
Mat img;
try
{
img = CvInvoke.Imread(openFileDialog1.FileName,LoadImageType.AnyColor);
pictureBox1.ImageLocation = openFileDialog1.FileName;
pictureBox1.Show();
}
catch
{
MessageBox.Show(String.Format("Invalide File: {0}", openFileDialog1.FileName));
return;
}
UMat uImg = img.ToUMat(AccessType.ReadWrite);
ProcessImage(uImg);
}
}
private void ProcessImage(IInputOutputArray image)
{
try
{
Stopwatch watch = Stopwatch.StartNew(); // time the detection process
List<IInputOutputArray> licensePlateImagesList = new List<IInputOutputArray>();
List<IInputOutputArray> filteredLicensePlateImagesList = new List<IInputOutputArray>();
List<RotatedRect> licenseBoxList = new List<RotatedRect>();
List<string> words = _licensePlateDetector.DetectLicensePlate(
image,
licensePlateImagesList,
filteredLicensePlateImagesList,
licenseBoxList);
watch.Stop(); //stop the timer
Point startPoint = new Point(10, 10);
for (int i = 0; i < words.Count; i++)
{
Mat dest = new Mat();
CvInvoke.VConcat(licensePlateImagesList[i], filteredLicensePlateImagesList[i], dest);
AddLabelAndImage(
ref startPoint,
String.Format("License: {0}", words[i]),
dest, Stopwatch.GetTimestamp());
PointF[] verticesF = licenseBoxList[i].GetVertices();
Point[] vertices = Array.ConvertAll(verticesF, Point.Round);
using (VectorOfPoint pts = new VectorOfPoint(vertices))
CvInvoke.Polylines(image, pts, true, new Bgr(Color.Red).MCvScalar, 2);
}
}
finally
{
//_timer.Start();
}
}
private void AddLabelAndImage(ref Point startPoint, String labelText, IImage image, long totalSeconds)
{
pictureBox2.Image = image.Bitmap;
label1.Text = labelText + "\r\n"+ label1.Text ;
}
...
