private void CorrectLevels()
{
ImageStatistics ims = new ImageStatistics(_recogimg);
Histogram gr = ims.Gray;
double median = gr.Median;
double mean = gr.Mean;
double stdev = gr.StdDev;
//30 170 10
//for (int i = 30; i < 170; i += 10)
//{
// this.CorrectLevel(i, (int)mean);
// ims = new ImageStatistics(_recogimg);
// gr = ims.Gray;
// stdev = gr.StdDev;
// mean = gr.Mean;
// if (stdev >= 65 & mean >= 220) { break; }
//}
BradleyLocalThresholding filter = new BradleyLocalThresholding();
// apply the filter
filter.ApplyInPlace(_recogimg);
}
public void bradley(ref Bitmap tmp)
{
BradleyLocalThresholding filter = new BradleyLocalThresholding();
// filter.AssertCanApply(tmp.PixelFormat);
filter.ApplyInPlace(tmp);
}
private Image <Gray, Byte> prepareImg2(System.Drawing.Image img, int threshold, bool invertImg)
{
Image <Gray, Byte> GrayImg = new Image <Gray, byte>((Bitmap)img);
EmgImgProcssing = new ImageProcessing_Emgu();
// create the filter
BradleyLocalThresholding filter2 = new BradleyLocalThresholding();
// apply the filter
filter2.ApplyInPlace(GrayImg.Bitmap);
GrayImg = GrayImg.Erode(1).Dilate(5).Erode(1);
// create filter
Invert filter3 = new Invert();
// apply the filter
filter3.ApplyInPlace(GrayImg.Bitmap);
return(GrayImg);
}
private void process()
{
stopwatch.Reset();
stopwatch.Start();
plates = new List <string>();
frame = contrastCorrectionFilter.Apply(originalImage);
frame = grayscaleFilter.Apply(frame);
BitmapData frameData = frame.LockBits(new Rectangle(0, 0, frame.Width, frame.Height), ImageLockMode.ReadWrite, frame.PixelFormat);
UnmanagedImage data = new UnmanagedImage(frameData);
bradleyLocalFilter.ApplyInPlace(data);
fillHoles.ApplyInPlace(data);
openingFilter.ApplyInPlace(data);
blobCounter.ProcessImage(data);
data.Dispose();
frame.UnlockBits(frameData);
Graphics g = Graphics.FromImage(originalImage);
Blob[] blobs = blobCounter.GetObjectsInformation();
foreach (Blob blob in blobs)
{
List <IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blob);
List <IntPoint> corners = null;
// da li je četverougao?
if (!shapeChecker.IsQuadrilateral(edgePoints, out corners))
{
continue;
}
if (FindNewCornersAndCheckAspectRatio(corners))
{
SimpleQuadrilateralTransformation sqt = new SimpleQuadrilateralTransformation(corners, 300, 66);
Bitmap plate = sqt.Apply(originalImage);
plate = grayscaleFilter.Apply(plate);
otsuThresholdFilter.ApplyInPlace(plate);
if (!IsLicensePlate(plate))
{
continue;
}
String plateText;
if (FindText(plate, out plateText))
{
g.DrawPolygon(pen, ToPointsArray(corners));
frame = plate;
plates.Add(plateText);
}
}
}
g.Dispose();
stopwatch.Stop();
}
private static Bitmap PreProcess(Bitmap bmp)
{
Grayscale gfilter = new Grayscale(0.2125, 0.7154, 0.0721);
Invert ifilter = new Invert();
BradleyLocalThresholding thfilter = new BradleyLocalThresholding();
bmp = gfilter.Apply(bmp);
thfilter.ApplyInPlace(bmp);
ifilter.ApplyInPlace(bmp);
return(bmp);
}
// source
// http://stackoverflow.com/questions/35980717/why-doesnt-aforge-net-blobcounter-getobjectsinformation-detect-objects
private Bitmap PreProcess(Bitmap bmp)
{
//Those are AForge filters "using Aforge.Imaging.Filters;"
Grayscale gfilter = new Grayscale(0.2125, 0.7154, 0.0721);
Invert ifilter = new Invert();
BradleyLocalThresholding thfilter = new BradleyLocalThresholding();
bmp = gfilter.Apply(bmp);
thfilter.ApplyInPlace(bmp);
ifilter.ApplyInPlace(bmp);
return(bmp);
}
/// <summary>
/// 设置图片为黑白色
/// </summary>
/// <param name="img"></param>
/// <returns></returns>
public static System.Drawing.Image BlackWhitePhoto(Bitmap map)
{
if (map.PixelFormat != PixelFormat.Format8bppIndexed)
{
var bitmap = ReplaceBackgroundColor(map, Color.White);
Grayscale g = new Grayscale(0.2125, 0.7154, 0.0721);
bitmap = g.Apply(bitmap);
BradleyLocalThresholding filter = new BradleyLocalThresholding();
filter.ApplyInPlace(bitmap);
return(bitmap);
}
return(map);
}
public void ProcessImage(Bitmap input_image)
{
lock (balanceLock)
{
int side = Math.Min(input_image.Height, input_image.Width);
Rectangle cropRect = new Rectangle(0, 0, side, side); // this is square that represents feed from camera
g.DrawImage(input_image, new Rectangle(0, 0, input_image.Width, input_image.Height), cropRect, GraphicsUnit.Pixel); // place it on original bitmap
// set new processed
if (processed != null)
{
processed.Dispose();
}
// Конвертируем изображение в градации серого
processed = grayFilter.Apply(AForge.Imaging.UnmanagedImage.FromManagedImage(original));
// Пороговый фильтр применяем. Величина порога берётся из настроек, и меняется на форме
threshldFilter.PixelBrightnessDifferenceLimit = ThresholdValue;
threshldFilter.ApplyInPlace(processed);
InvertFilter.ApplyInPlace(processed);
Blober.ProcessImage(processed);
AForge.Imaging.Blob[] blobs = Blober.GetObjectsInformation();
BlobCount = blobs.Length;
if (blobs.Length > 0)
{
var BiggestBlob = blobs[0];
Recongnised = true;
Blober.ExtractBlobsImage(processed, BiggestBlob, false);
processed = BiggestBlob.Image;
AForge.Point mc = BiggestBlob.CenterOfGravity;
AForge.Point ic = new AForge.Point((float)BiggestBlob.Image.Width / 2, (float)BiggestBlob.Image.Height / 2);
AngleRad = (ic.Y - mc.Y) / (ic.X - mc.X);
Angle = (float)(Math.Atan(AngleRad) * 180 / Math.PI);
}
else
{
// TODO make arrengaments for No blobs case
Recongnised = false;
Angle = 0;
AngleRad = -1;
}
if (number != null)
{
number.Dispose();
}
number = processed.ToManagedImage();
}
}
public static System.Drawing.Image BlackWhitePhoto(System.Drawing.Image images)
{
try
{
Bitmap map = new Bitmap(images);
Bitmap bitmap = new Bitmap(images.Width, images.Height);
if (bitmap.PixelFormat != PixelFormat.Format8bppIndexed)
{
bitmap = Grayscale.CommonAlgorithms.BT709.Apply(map);
//Grayscale g = new Grayscale(0.2125, 0.7154, 0.0721);
//bitmap = g.Apply(map);
}
BradleyLocalThresholding filter = new BradleyLocalThresholding();
filter.ApplyInPlace(bitmap);
return(bitmap);
}
catch (Exception ex)
{
throw ex;
}
}
/// <summary>
/// Processes the specified image.
/// </summary>
/// <param name="image">The image.</param>
/// <remarks></remarks>
public void Process(Bitmap image)
{
//Graphics g = Graphics.FromImage(image);
/*
* float area = image.Width * image.Height;
* float borderWidth = (float)Math.Max(3, Math.Round(0.25 * (area / 1024)));
*
* g.DrawRectangle(new Pen(Color.Black, borderWidth), 0, 0, image.Width - 1, image.Height - 1);
* g.Dispose();
*/
image = grayscale.Apply(image);
//ContrastStretch filter = new ContrastStretch();
//HistogramEqualization filter = new HistogramEqualization();
//ContrastCorrection filter = new ContrastCorrection(0.5);
//BrightnessCorrection filter = new BrightnessCorrection(-0.15);
//GammaCorrection filter = new GammaCorrection(1.5);
//filter.ApplyInPlace(image);
threshold.ApplyInPlace(image);
invert.ApplyInPlace(image);
float sideAvg = (image.Width + image.Height) / 2;
float borderWidth = (float)Math.Max(2, Math.Round(0.02 * sideAvg));
Bitmap temp = new Bitmap(image.Width, image.Height);
Graphics g = Graphics.FromImage(temp);
g.DrawImageUnscaled(image, 0, 0);
g.DrawRectangle(new Pen(Color.White, borderWidth), 0, 0, image.Width - 1, image.Height - 1);
g.Dispose();
image = (new Threshold()).Apply(grayscale.Apply(temp));
floodFill.StartingPoint = new IntPoint(0, 0);
floodFill.ApplyInPlace(image);
blobCounter.ProcessImage(image);
Blob[] blobs = blobCounter.GetObjectsInformation();
//Results = new List<OCRResult>();
Results.Clear();
foreach (Blob b in blobs)
{
int w = b.Rectangle.Width;
int h = b.Rectangle.Height;
if (w > 16 && h > 16 && h < 24)
{
w = 16;
h = 16;
}
else
//{
if (!(w >= 3 && w <= 5 && h >= 14 && h <= 17 && b.Fullness > 0.6f))
{
//Bitmap test = image.Clone(new Rectangle(b.Rectangle.X, b.Rectangle.Y, w, h), PixelFormat.Format24bppRgb);
if (b.Area < 20 || b.Fullness < 0.2f || b.Fullness > 0.9f || h > 18)
{
continue;
}
}
//}
//blobCounter.MinWidth = 3;
//blobCounter.MinHeight = 10;
//if (b.Area < 20 || b.Fullness > 0.9f) continue;
Bitmap slice = image.Clone(new Rectangle(b.Rectangle.X, b.Rectangle.Y, w, h), PixelFormat.Format24bppRgb);
slice = grayscale.Apply(slice);
slice = resize.Apply(slice);
dilate.ApplyInPlace(slice);
if (Recognise)
{
Result res = classifier.Classify(new Instance("?", BitmapFeatureExtract(slice)));
Results.Add(new OCRResult(b, slice, res.Class, res.Value.ToString()));
}
else
{
Results.Add(new OCRResult(b, slice, "?", ""));
}
}
}
static void Main(string[] args)
{
Console.Title = "Basic OCR.exe";
string filename, path, dir, language;
//take full path from user
Console.WriteLine("Enter path:");
//Separating filename and directory
path = Console.ReadLine();
dir = Path.GetDirectoryName(path);
filename = Path.GetFileNameWithoutExtension(path);
//Enter language for Tesseract engine
Console.WriteLine("Enter language(hin-Hindi,eng-English,ori-Oriya):");
language = Console.ReadLine();
//Create Bitmap object
Bitmap img2 = Accord.Imaging.Image.FromFile(path);
//Image is first converted to Grayscale as Thresholding doesn't support coloured images as input
Grayscale gray = new Grayscale(0.2125, 0.7154, 0.0721);
Bitmap result = gray.Apply(img2);
// This blackens the whole area in shades: Threshold thres = new Threshold(100);
/*
* Applying Bradley Thresholding which brightens up the area in shades hence a uniformly bright
* image is obtained.
*/
Console.WriteLine("Applying Bradley Local Thresholding...");
BradleyLocalThresholding thres = new BradleyLocalThresholding();
thres.WindowSize = 80;
thres.PixelBrightnessDifferenceLimit = 0.1F;
thres.ApplyInPlace(result);
//Save the binarized image
result.Save(dir + "\\" + filename + "_1thres.bmp");
//Sharpening
Console.WriteLine("Sharpening...");
Sharpen sharp = new Sharpen();
// apply the filter
sharp.ApplyInPlace(result);
//result.Save(dir + "\\" + filename + "_2sharp.bmp");
//Bilateral Smoothing
// create filter
Console.WriteLine("Applying Bilateral smoothing...");
BilateralSmoothing smooth = new BilateralSmoothing();
smooth.KernelSize = 7;
smooth.SpatialFactor = 10;
smooth.ColorFactor = 60;
smooth.ColorPower = 0.5;
// apply the filter
smooth.ApplyInPlace(result);
//Save cleaned image
//result.Save(dir + "\\" + filename + "_3smooth.bmp");
//Document skew, line detection
DocumentSkewChecker skew = new DocumentSkewChecker();
double angle = skew.GetSkewAngle(result);
Console.WriteLine("Skewing and rotating...");
RotateBilinear rot = new RotateBilinear(-angle);
rot.FillColor = Color.White;
result = rot.Apply(result);
result.Save(dir + "\\" + filename + "_4rot.bmp");
try
{
using (var engine = new TesseractEngine(@".\tessdata", language, EngineMode.Default))
{
using (var img = result)
{
using (var page = engine.Process(img))
{
var text = page.GetText();
//Console.WriteLine("Text(get text): \r\n{0}", text);
StreamWriter sw;
string Filename = dir + "\\" + filename + "_text.doc";
sw = File.CreateText(Filename);
Console.WriteLine("Generating file...");
string FileData = text;
sw.WriteLine(FileData);
sw.Close();
//We make a list of type Rectangle. It stores data of all the bounding boxes
List <Rectangle> boxes = page.GetSegmentedRegions(PageIteratorLevel.Symbol);
/*
* Graphics gives the following error in case of result/img:
* A Graphics object cannot be created from an image that has an indexed pixel format. ...
* ...System.Exception: A Graphics object cannot be created from an image that has an indexed pixel format.
*
* I am using the following solution for now:
*/
Bitmap rez = new Bitmap(result);
using (Graphics g = Graphics.FromImage(rez))
{
Pen p = new Pen(Brushes.Red, 1.0F);
foreach (Rectangle r in boxes)
{
//Console.WriteLine(r);
g.DrawRectangle(p, r);
}
g.DrawImage(rez, 0, 0);
}
//Saving the image with bounding boxes
Console.WriteLine("Generating image with bounding boxes...");
rez.Save(dir + "\\" + filename + "_5seg.bmp");
}
}
}
}
catch (Exception e)
{
Trace.TraceError(e.ToString());
Console.WriteLine(e.Message);
Console.WriteLine(e.ToString());
}
finally
{
Console.WriteLine("\n\nPress ENTER/RETURN to exit");
Console.ReadKey(true);
}
}