private void videoNewFrame(object sender, NewFrameEventArgs eventArgs)
{
Bitmap bitmap = (Bitmap)eventArgs.Frame.Clone();
Threshold thresholdFilter = new Threshold(120);
Grayscale grayscaleFilter = new Grayscale(0.2, 0.7, 0.07);
BrightnessCorrection brightnessFilter = new BrightnessCorrection(brightnessVal);
ContrastCorrection contrastFilter = new ContrastCorrection(contrastVal);
SaturationCorrection saturationFilter = new SaturationCorrection(saturationVal);
bitmap = brightnessFilter.Apply((Bitmap)bitmap.Clone());
bitmap = contrastFilter.Apply((Bitmap)bitmap.Clone());
bitmap = saturationFilter.Apply((Bitmap)bitmap.Clone());
if (isGray)
{
bitmap = grayscaleFilter.Apply((Bitmap)bitmap.Clone());
}
if (isBW)
{
bitmap = grayscaleFilter.Apply((Bitmap)bitmap.Clone());
bitmap = thresholdFilter.Apply(bitmap);
}
currentFrame = (Bitmap)bitmap.Clone();
if (fileWriter != null)
{
fileWriter.WriteVideoFrame((Bitmap)bitmap.Clone());
}
}
private void btnOperation(object sender, RoutedEventArgs e)
{
var master = sender as System.Windows.Controls.Button;
switch (master.Name)
{
case ("btnThreshold"):
var parmTh = (int)nudThreshold.Value;
SrcMImg = SrcMImg.Add(Threshold.Apply(parmTh), StrThreshold.With(parmTh));
break;
case ("btnAdpThreshold"):
var parmAdTh = (int)nudAdpThreshold.Value;
SrcMImg = SrcMImg.Add(AdpTHreshold.Apply(parmAdTh), StrAdpTHreashold.With(parmAdTh));
break;
case ("btnMedian"):
var parmMdn = (int)nudMedian.Value;
SrcMImg = SrcMImg.Add(Median.Apply(parmMdn), StrMedian.With(parmMdn));
break;
case ("btnNormalize"):
var parmNorm = (int)nudNormalize.Value;
SrcMImg = SrcMImg.Add(Normalize.Apply(parmNorm), StrNormalize.With(parmNorm));
break;
}
imgBack.Source = ToBitmapSource(SrcMImg.GetLastValue());
txbLog.Selection.Text = SrcMImg.GetLastPaper().Paper2TextHistory();
var temp = SrcMImg.GetLastPaper().Paper2TextHistory();
}
private void blackAndWhiteToolStripMenuItem_Click(object sender, EventArgs e)
{
Threshold thresholdObj = new Threshold();
blackNwhiteImage = thresholdObj.Apply(grayImage);
pictureBox4.Image = blackNwhiteImage;
}
public string decoder(Bitmap img)
{
//灰度
Grayscale grayscaleFilter = new Grayscale(0.299, 0.587, 0.114);
Bitmap bitmapGrayscale = grayscaleFilter.Apply(img);
//二值化
Threshold thresholdFilter = new Threshold(128);
Bitmap bitmapThreshold = thresholdFilter.Apply(bitmapGrayscale);
/////统计点数分布
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(bitmapThreshold);
Histogram histogram = his.Gray;
int[] dato = histogram.Values;
/////分割验证码字符
charCut(dato);
////////解码
yuantongdecoder decode = new yuantongdecoder();
string backNumber = decode.Decoder(bitmapThreshold, div);
return(backNumber);
}
public void RunThreshold(int threshold, bool showGrayScale)
{
using (Bitmap newBitmap = LoadBitmap())
{
Rectangle rect = new Rectangle(0, 0, newBitmap.Width, newBitmap.Height);
using (UnmanagedImage image = new UnmanagedImage(newBitmap.LockBits(rect, ImageLockMode.ReadWrite, newBitmap.PixelFormat)))
{
using (UnmanagedImage grayImage = UnmanagedImage.Create(image.Width, image.Height, PixelFormat.Format8bppIndexed))
{
Grayscale.CommonAlgorithms.BT709.Apply(image, grayImage);
if (showGrayScale)
{
ImageForm.ShowImageDialog("Gray scale", grayImage);
}
Threshold thresholdFilter = new Threshold(threshold);
using (UnmanagedImage thresholdImage = thresholdFilter.Apply(grayImage))
{
ImageForm.ShowImageDialog("Threshold", thresholdImage);
}
}
}
}
}
public Bitmap ThreseHoldImage(Bitmap bmp)
{
Threshold filter = new Threshold(100);
Bitmap blackenedImage = filter.Apply(bmp);
return(blackenedImage);
}
public static Maybe <ProcFuncs> ConvertToPreProFunc(ProcRecipe src)
{
var name = src.Item1;
var strparm = src.Item2;
int parameter;
if (!Int32.TryParse(strparm, out parameter))
{
return(None);
}
switch (name)
{
case keyThreshold:
return(Threshold.Apply(parameter));
case keyNormalize:
return(Normalize.Apply(parameter));
case keyAdpThreshold:
return(AdpThreshold.Apply(parameter));
case keyMedian:
return(Median.Apply(parameter));
default:
return(None);
}
}
private void btnBinaryYap_Click(object sender, EventArgs e)
{
Bitmap image = new Bitmap(pictureBox1.Image);
Threshold threshold = new Threshold();
pictureBox4.Image = threshold.Apply(Grayscale.CommonAlgorithms.BT709.Apply(image));
}
private Bitmap getThresholdedFrame(Bitmap grayscaledFrame)
{
Threshold filter = new Threshold(18);
Bitmap thresholdedFrame = filter.Apply(grayscaledFrame);
return(thresholdedFrame);
}
private Bitmap XXX(Bitmap bmpBefore, Bitmap bmpAfter)
{
var filter = new Grayscale(0.2125, 0.7154, 0.0721);
bmpBefore = filter.Apply(bmpBefore);
bmpAfter = filter.Apply(bmpAfter);
// create filters
var differenceFilter = new Difference();
IFilter thresholdFilter = new Threshold(15);
// set backgroud frame as an overlay for difference filter
differenceFilter.OverlayImage = bmpBefore;
// apply the filters
Bitmap tmp1 = differenceFilter.Apply(bmpAfter);
Bitmap tmp2 = thresholdFilter.Apply(tmp1);
IFilter erosionFilter = new Erosion();
// apply the filter
Bitmap tmp3 = erosionFilter.Apply(tmp2);
IFilter pixellateFilter = new Pixellate();
// apply the filter
Bitmap tmp4 = pixellateFilter.Apply(tmp3);
return(tmp4);
}
public string decodeBitmap(Bitmap img)
{
/////////图像处理
//转为灰度图
Grayscale grayscaleFilter = new Grayscale(0.299, 0.587, 0.114);
Bitmap bitmapGrayscale = grayscaleFilter.Apply(img);
//二值化
Threshold thresholdFilter = new Threshold(128);
Bitmap bitmapThreshold = thresholdFilter.Apply(bitmapGrayscale);
////////中值滤波
Median mediafil = new Median();
Bitmap medianBit = mediafil.Apply(bitmapThreshold);
//锐化
Sharpen sharpPic = new Sharpen();
Bitmap sharpOut = sharpPic.Apply(medianBit);
//统计点数
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(sharpOut);
Histogram histogram = his.Gray;
int[] dato = histogram.Values;
/////分割图像
charCut(dato);
shunfengdecoder decode = new shunfengdecoder();
string backcode = decode.Decoder(sharpOut, div);
return(backcode);
}
private void detectSkin()
{
//skin detection
Color clr = Color.FromArgb(Color.White.ToArgb());
Color clr1 = Color.FromArgb(Color.Black.ToArgb());
int imgHeight = imageGot.Height;
int imgWidth = imageGot.Width;
String sc = "";
var rect = new Rectangle(0, 0, imgWidth, imgHeight);
var data = imageGot.LockBits(rect, ImageLockMode.ReadWrite, imageGot.PixelFormat);
var depth = Bitmap.GetPixelFormatSize(data.PixelFormat) / 8; //bytes per pixel
var buffer = new byte[data.Width * data.Height * depth];
//copy pixels to buffer
Marshal.Copy(data.Scan0, buffer, 0, buffer.Length);
ProcessDetectSkin(buffer, 0, 0, data.Width, data.Height, data.Width, depth);
//Copy the buffer back to image
Marshal.Copy(buffer, 0, data.Scan0, buffer.Length);
imageGot.UnlockBits(data);
GrayscaleBT709 gs = new GrayscaleBT709();
imageGot = gs.Apply(imageGot);
Threshold th = new Threshold();
imageGot = th.Apply(imageGot);
}
private void blackNWhiteToolStripMenuItem_Click(object sender, EventArgs e)
{
Threshold gb = new Threshold();
newImg = gb.Apply(newImg);
pictureBox3.Image = newImg;
}
private void button2_Click_1(object sender, EventArgs e)
{
OpenFileDialog openDialog = new OpenFileDialog();
var returnValue = openDialog.ShowDialog();
if (returnValue == DialogResult.OK)
{
originalImage = new Bitmap(openDialog.FileName);
pictureBox1.Image = originalImage;
// pictureBox4.SizeMode = PictureBoxSizeMode.StretchImage;
Grayscale GrayImage = new Grayscale(0.2125, 0.7154, 0.0721);
Bitmap graycolor = GrayImage.Apply(originalImage);
Threshold BinaryImageE = new Threshold();
Bitmap binaryimage = BinaryImageE.Apply(graycolor);
pictureBox1.Image = graycolor;
//graycolor.Save(@"E:\Works\Machine Learning - OCR\raw\graycolor.jpg");
List <Bitmap> temp_bound = new List <Bitmap>();
//Bitmap boundedimage1 = new Bitmap("E://Works//Machine Learning - OCR//raw//graycolor.jpg");
temp_bound.Add(graycolor);
List <Bitmap> boundedimage = BoundImage(temp_bound);
pictureBox2.Image = boundedimage[0];
//boundedimage[0].Save(@"E:\Works\Machine Learning - OCR\raw\boundedimage.jpg");
List <Bitmap> segments = Segment(boundedimage[0]);
pictureBox2.Image = segments[0];
List <float[]> test_feature = Zone(segments);
write_testfile(test_feature);
TestClassifier();
}
}
/// <summary>
/// 根据图片的纵横灰度情况截取图片
/// 使用Aforge类库
/// </summary>
/// <param name="image"></param>
/// <returns></returns>
public static Rectangle GetByGrayPoint(Bitmap image)
{
//灰度化
Grayscale g = new Grayscale(0.2125, 0.7154, 0.0721);
// apply the filter
var grayImg = g.Apply(image);
//二值化
var threshold = new Threshold();
threshold.ThresholdValue = 80;
var thresholdImage = threshold.Apply(grayImg);
//找出纵横灰度值
HorizontalIntensityStatistics hs = new HorizontalIntensityStatistics(thresholdImage);
VerticalIntensityStatistics vs = new VerticalIntensityStatistics(thresholdImage);
var vThreshold = (image.Height / 4) * 255;
var hThreshold = (image.Width / 4) * 255;
var hGrays = hs.Gray.Values.ToList();
var vGrays = vs.Gray.Values.ToList();
var hmin = FindPaperBorder(hGrays, true, hThreshold, 0);
var hmax = FindPaperBorder(hGrays, false, hThreshold, 0);
var vmin = FindPaperBorder(vGrays, true, vThreshold, 0);;
var vmax = FindPaperBorder(vGrays, false, vThreshold, 0);
return(new Rectangle(hmin, vmin, hmax - hmin, vmax - vmin));
}
private Bitmap preProcess(Bitmap originalImage)
{
Invert invertObj = new Invert();
Bitmap invertImage = invertObj.Apply((Bitmap)originalImage.Clone());
invertImage = Grayscale.CommonAlgorithms.BT709.Apply(invertImage);
Threshold bwObject = new Threshold();
invertImage = bwObject.Apply(invertImage);
ExtractBiggestBlob blobObject = new ExtractBiggestBlob();
invertImage = blobObject.Apply(invertImage);
ResizeBicubic resize = new ResizeBicubic(60, 90);
invertImage = resize.Apply(invertImage);
//CannyEdgeDetector edgeDetector = new CannyEdgeDetector();
//invertImage = edgeDetector.Apply(invertImage);
return(invertImage);
}
void VideoSourcePlayerNewFrame(object sender, ref Bitmap image)
{
lock (this)
{
Bitmap img_copy = new Bitmap(image);
Grayscale gray_filter = new Grayscale(0.2125, 0.7154, 0.0721);
img_copy = gray_filter.Apply(img_copy);
Threshold thresh = new Threshold(thresh_val);
img_copy = thresh.Apply(img_copy);
BlobCounter bc = new BlobCounter();
bc.FilterBlobs = true;
bc.MinHeight = min_size_val;
bc.MinWidth = min_size_val;
bc.MaxHeight = min_size_val + 50;
bc.MaxWidth = min_size_val + 50;
bc.ProcessImage(img_copy);
Rectangle[] rects = bc.GetObjectsRectangles();
Graphics g = videoSourcePlayer.CreateGraphics();
using (Pen p = new Pen(Color.Red))
{
foreach (Rectangle r in rects)
{
g.DrawRectangle(p, r);
g.DrawString("a", new Font("Consolas", 10), Brushes.Red, r.X, r.Y);
}
}
image = img_copy;
}
}
private void button4_Click(object sender, EventArgs e)
{
int.TryParse(textBox1.Text, out Threshold);
BinFilter.ThresholdValue = Threshold;
BinBmp = BinFilter.Apply(grayBmp);
process.Image = BinBmp;
this.Text = Threshold.ToString();
}
public IImage Apply(IImage image)
{
var grayScale = ToGrayScale(image);
var filter = new Threshold(factor);
var bmp = filter.Apply(grayScale.ToGray().Lock().AsAForgeImage());
return(bmp.AsImage());
}
private void otsuÇıkarımToolStripMenuItem_Click(object sender, EventArgs e)
{
Threshold filter = new Threshold(100);
// apply the filter
Bitmap otsu = filter.Apply((Bitmap)pictureBox7.Image);
pictureBox8.Image = otsu;
}
private void binarToolStripMenuItem_Click(object sender, EventArgs e)
{
GrayscaleBT709 grayoject = new GrayscaleBT709();
pictureBox2.Image = grayoject.Apply((Bitmap)pictureBox1.Image);
Threshold filter = new Threshold();
pictureBox2.Image = filter.Apply((Bitmap)pictureBox2.Image);
}
/// <summary>
/// Generate a binary BitmapImage
/// </summary>
/// <param name="bitmapImage"></param>
/// <param name="thresholdLevel"></param>
/// <returns></returns>
public static BitmapImage Binary(this BitmapImage bitmapImage, int thresholdLevel)
{
Bitmap bitmap = bitmapImage.BitmapImage2Bitmap();
Threshold threshold = new Threshold(thresholdLevel);
IFilter filter = Grayscale.CommonAlgorithms.BT709;
bitmap = filter.Apply(bitmap);
return(threshold.Apply(bitmap).ToBitmapImage());
}
public void Binarize(object sender, DoWorkEventArgs e)
{
Bitmap InputImage = null;
if (inPutRb.Checked)
{
InputImage = Accord.Imaging.Filters.Grayscale.CommonAlgorithms.BT709.Apply((Bitmap)input_PB.Image.Clone());
}
else if (outPutRB.Checked)
{
InputImage = (Bitmap)outputImageBox.Image.Clone();
}
if (wolfRb.Checked)
{
var wolfFilter = new Accord.Imaging.Filters.WolfJolionThreshold();
if (holderTb_1.Text != String.Empty)
{
wolfFilter.K = double.Parse(holderTb_1.Text);
}
if (holderTb_2.Text != String.Empty)
{
wolfFilter.R = double.Parse(holderTb_2.Text);
}
if (holderTb_3.Text != String.Empty)
{
wolfFilter.Radius = int.Parse(holderTb_3.Text);
}
Bitmap raw_img = InputImage;
UnmanagedImage res = wolfFilter.Apply(UnmanagedImage.FromManagedImage(raw_img));
outputImageBox.Image.Dispose();
outputImageBox.Image = res.ToManagedImage();
}
else if (simpleThresh.Checked)
{
int Thresh = int.Parse(holderTb_1.Text);
var simpleThresh = new Threshold();
simpleThresh.ThresholdValue = Thresh;
Bitmap raw_img = InputImage;
UnmanagedImage res = simpleThresh.Apply(UnmanagedImage.FromManagedImage(raw_img));
outputImageBox.Image.Dispose();
outputImageBox.Image = res.ToManagedImage();
}
else if (OtsuRb.Checked)
{
int Thresh = int.Parse(holderTb_1.Text);
var OtsuThresh = new Threshold();
OtsuThresh.ThresholdValue = Thresh;
Bitmap raw_img = InputImage;
UnmanagedImage res = OtsuThresh.Apply(UnmanagedImage.FromManagedImage(raw_img));
outputImageBox.Image.Dispose();
outputImageBox.Image = res.ToManagedImage();
}
}
public Bitmap GetNewFrame(Bitmap source)
{
// get grayscale image
var source1 = Grayscale.CommonAlgorithms.RMY.Apply(source);
var newFrame = threshold.Apply(source1);
source.Dispose();
source1.Dispose();
return(newFrame);
}
private void thresoldToolStripMenuItem_Click(object sender, EventArgs e)
{
if (pictureBox1.Image != null)
{
Threshold thresold = new Threshold((int)trackBartThresold.Value);
Bitmap org = new Bitmap(pictureBox1.Image);
Bitmap clone = org.Clone(new Rectangle(0, 0, org.Width, org.Height), PixelFormat.Format24bppRgb);
pictureBox2.Image = thresold.Apply(clone);
}
}
private void trackBartThresold_Scroll(object sender, EventArgs e)
{
if (pictureBox1.Image != null)
{
Threshold thresold = new Threshold((int)trackBartThresold.Value);
Bitmap org = new Bitmap(pictureBox1.Image);
Bitmap clone = org.Clone(new Rectangle(0, 0, org.Width, org.Height), PixelFormat.Format8bppIndexed);
pictureBox2.Image = thresold.Apply(clone);
}
}
public EdgeImage Generate(Bitmap source)
{
// Make GrayScale Version of image
Grayscale filter = new Grayscale(0.2125, 0.7154, 0.0721);
Bitmap grayImage = filter.Apply(source);
// Apply Sobel Edge Detection to the image
SobelEdgeDetector sobelFilter = new SobelEdgeDetector();
Bitmap edgeImage = sobelFilter.Apply(grayImage);
// Apply Threshold to edge detected image
// Edges are white pixels with value 255 otherwise black with value 0
Threshold thresholdFilter = new Threshold(Threshold);
Bitmap thresholdImage = thresholdFilter.Apply(edgeImage);
// Render Image
var newImg = new Bitmap(thresholdImage.Width, thresholdImage.Height);
if (thresholdImage != null)
{
var g = Graphics.FromImage(newImg);
var srcRect = new Rectangle(0, 0, thresholdImage.Width, thresholdImage.Height);
var destRect = new Rectangle(0, 0, thresholdImage.Width, thresholdImage.Height);
g.DrawImage(thresholdImage, destRect, srcRect, GraphicsUnit.Pixel);
}
var edgeLocations = new List <PixelCoordinates>();
// Save location of edges
for (int x = 0; x < newImg.Width; x++)
{
for (int y = 0; y < newImg.Height; y++)
{
if (newImg.GetPixel(x, y).R >= Threshold)
{
edgeLocations.Add(new PixelCoordinates()
{
X = x, Y = y
});
}
}
}
// Dispose of the created images
grayImage.Dispose();
edgeImage.Dispose();
thresholdImage.Dispose();
return(new EdgeImage()
{
Image = newImg, Edges = edgeLocations
});
}
//-------------------------------------------------------------
private void process_imginput(Bitmap img, String Plate_Type)
{
//grayscale
IFilter way_filt;//= new GrayscaleY();
//process_image = way_filt.Apply(img);
//resize
if (Plate_Type == "1hang")
{
way_filt = new ResizeBilinear(600, 120); //bien 1 hang
}
else
{
way_filt = new ResizeBilinear(300, 200); //bien 2 hang
}
process_image = way_filt.Apply(img);
//process_image = get_plate(process_image, 10, 210, 30, 330);
input_image = way_filt.Apply(input_image);
p = process_image;
//threshold
way_filt = new Threshold(125);
process_image = way_filt.Apply(process_image);
//K-means
process_image = kmean(process_image);
//invert
way_filt = new Invert();
process_image = way_filt.Apply(process_image);
//liembt
//UCM
way_filt = new Median();
process_image = way_filt.Apply(process_image);
//way_filt = new AdaptiveSmooth();
//process_image = way_filt.Apply(process_image);
//end liembt
//filter k
BlobsFiltering filter = new BlobsFiltering();
filter.MinHeight = 25;//50
filter.MinWidth = 10;
filter.MaxHeight = 100;
filter.ApplyInPlace(process_image);
//p = process_image;
input_width = process_image.Width;
input_height = process_image.Height;
}
/// <summary>
/// Binarize image with threshold filter
/// </summary>
/// <param name="image"></param>
/// <param name="threshold">threshold for binarization</param>
public static Bitmap Threshold(this Bitmap image, byte threshold)
{
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new NotSupportedException("Filter can be applied to binary 8bpp images only");
}
Threshold thresholdFilter = new Threshold(threshold);
return(thresholdFilter.Apply(image));
}
public static Bitmap Binaryzation(Bitmap b, int limit)
{
Threshold th = new Threshold();
th.ThresholdValue = limit;
Bitmap bx = ImageSupporter.ColorToGrayscale((Bitmap)b.Clone());
GrayscaleToRGB grayscaleToRGB = new GrayscaleToRGB();
return(grayscaleToRGB.Apply(th.Apply(ImageSupporter.ColorToGrayscale(bx))));
}