/// <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 void DoHistogram()
{
swHistogram.Reset();
swHistogram.Start();
Log("Building Histogram");
AForge.Math.Histogram grayhist;
AForge.Math.Histogram Redhist;
AForge.Math.Histogram Greenhist;
AForge.Math.Histogram Bluehist;
// collect statistics
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(new Bitmap(pbImage.Image));
// get gray histogram (for grayscale image)
if (his.IsGrayscale)
{
grayhist = his.Gray;
}
else
{
Redhist = his.Red;
Greenhist = his.Green;
Bluehist = his.Blue;
DoRGBHistogram(Redhist, Greenhist, Bluehist);
}
// output some histogram's information
//Log("Histogram Mean = " + hist.Mean);
//Log("Histogram Min = " + hist.Min);
//Log("Histogram Max = " + hist.Max);
swHistogram.Stop();
Log("Histogram built in " + swHistogram.Elapsed);
}
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);
}
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 int decode()
{
initBitmap(img);
//bmp.Save("that.png");
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(img);
Histogram histogram = his.Blue;
int[] dato = histogram.Values;
charCut(dato);
return(Decoder(img));
}
private string decode(Bitmap img)
{
initBitmap(img);
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(img);
Histogram histogram = his.Blue;
int[] dato = histogram.Values;
charCut(dato);
return(Decoder(img));
}
/// <summary>
/// Build the Histogram for Supplied Image
/// </summary>
/// <param name="image">
/// String: Path to image that histogram is to be created out of
/// </param>
public void DoHistogram(string image)
{
CurrentImage = image; // Used for re-generating the histogram
bool IsGrayScale = AForge.Imaging.Image.IsGrayscale(new Bitmap(image));
dynamic IntensityStatistics = null; // Use dynamic (a little like var) to assign this variable which maybe of different types.
swHistogram.Reset();
swHistogram.Start();
histogramStatus("Creating Histogram");
AForge.Math.Histogram grayhist;
AForge.Math.Histogram Redhist;
AForge.Math.Histogram Greenhist;
AForge.Math.Histogram Bluehist;
// collect statistics
//NOTE: We have to use the braces on these statements see: http://stackoverflow.com/questions/2496589/variable-declarations-following-if-statements
if (IsHorizontalIntensity)
{
histogramStatus("Using HorizontalIntensityStatistics");
IntensityStatistics = new HorizontalIntensityStatistics(new Bitmap(image));
}
else
{
histogramStatus("Using VerticalIntensityStatistics");
IntensityStatistics = new VerticalIntensityStatistics(new Bitmap(image));
}
// get gray histogram (for grayscale image)
if (IsGrayScale)
{
grayhist = IntensityStatistics.Gray;
//TODO: DoGrayHistogram();
histogramStatus("Grayscale Histogram");
}
else
{
Redhist = IntensityStatistics.Red;
Greenhist = IntensityStatistics.Green;
Bluehist = IntensityStatistics.Blue;
DoRGBHistogram(Redhist, Greenhist, Bluehist);
histogramStatus("RGB Histogram");
}
swHistogram.Stop();
histogramCompleted("Histogram built in " + swHistogram.Elapsed);
}
private void SaveImage(Bitmap bmp)
{
seq++;
var fname = $@"D:\tmp\images\{seq}.bmp";
bmp.Save(fname);
var s = new ImageStatistics(bmp);
var v = new VerticalIntensityStatistics(bmp);
var h = new HorizontalIntensityStatistics(bmp);
File.AppendAllText(
@"D:\tmp\images\stat.csv",
$"{seq},"
+ $"{s.Gray.Mean},{s.Gray.StdDev},"
+ $"{v.Gray.Mean},{v.Gray.StdDev},"
+ $"{h.Gray.Mean},{h.Gray.StdDev},"
+ "\r\n");
}
/// <summary>
/// Gets the content.
/// </summary>
/// <param name="mincross">Минимальная разница яркости ячейки с кретсиком</param>
/// <param name="maxcross">Максимальная разница яркости ячейки с кретсиком</param>
public void GetContent(double mincross, double maxcross)
{
_content = false;
_neurocontent = CellContent.Free;
List <double> _lrange = new List <double>();
BitmapData data = _parentimage.LockBits(_rect, ImageLockMode.ReadWrite, _parentimage.PixelFormat);
VerticalIntensityStatistics vis = new VerticalIntensityStatistics(data);
histogram = vis.Gray;
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(data);
Histogram hhistogram = his.Gray;
List <double> _hrange = new List <double>();
_parentimage.UnlockBits(data);
for (int i = 8; i <= 15; i++)
{
_lrange.Add((histogram.Values[i] + hhistogram.Values[i]) / 2);
// _hrange.Add(hhistogram.Values[i]);
}
// _britnessdispertion = (1 - RecogCore.Statistics.Mean(_lrange) / histogram.Values.Max()) + (1 - RecogCore.Statistics.Mean(_hrange) / hhistogram.Values.Max());
_britnessdispertion = 1 - RecogCore.Statistics.Mean(_lrange) / histogram.Values.Max();
if (_britnessdispertion <= mincross)
{
_neurocontent = CellContent.Free; _content = false;
}
if (_britnessdispertion > mincross & _britnessdispertion <= maxcross)
{
_neurocontent = CellContent.Cross; _content = true;
}
if (_britnessdispertion > maxcross)
{
_neurocontent = CellContent.Miss; _content = false;
}
}
// Draw a histogram.
private void DrawHistogram(Bitmap img)
{
Color back_color = Color.White;
Invert filter = new Invert();
// apply the filter
Bitmap inv = filter.Apply(img);
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(inv);
AForge.Math.Histogram histogram = his.Gray;
int[] values = histogram.Values;
Color[] Colors = new Color[] {
Color.Red, Color.LightGreen, Color.Blue,
Color.Pink, Color.Green, Color.LightBlue,
Color.Orange, Color.Yellow, Color.Purple
};
gr.Clear(back_color);
// Draw the histogram.
using (Pen thin_pen = new Pen(Color.Black, 0))
{
for (int i = 0; i < values.Length; i++)
{
float f2 = 650F;
float fl = (float)values[i] / f2;
gr.DrawLine(thin_pen, i, 0, i, fl);
}
}
}
/// <summary>
/// Performs hand detection calculations
/// </summary>
/// <param name="bmp">The camera frame to be processed</param>
/// <returns>A bitmap representation of the detected hands</returns>
public static Bitmap Findhands(Bitmap bmp)
{
Bitmap test = new Bitmap(bmp.Width, bmp.Height);
Graphics g = Graphics.FromImage(test);
for (int j = 0; j < 2; j++)
{
Bitmap partial = bmp.Clone(new System.Drawing.Rectangle(j * bmp.Width / 2, 0, bmp.Width / 2, bmp.Height), bmp.PixelFormat);
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(partial);
VerticalIntensityStatistics vis = new VerticalIntensityStatistics(partial);
Histogram gray = his.Gray;
Histogram GrayY = vis.Gray;
double meanX;
double meanY;
int[] hisValues = (int[])his.Gray.Values.Clone();
int[] visValues = (int[])vis.Gray.Values.Clone();
List <int> lX = new List <int>();
List <int> lY = new List <int>();
for (int i = 0; i < hisValues.Length; i++)
{
if (hisValues[i] != 0)
{
hisValues[i] = (hisValues[i] / hisValues.Max()) * 255;
}
if (hisValues[i] == 0)
{
lX.Add(i + (j * test.Width / 2));
}
}
for (int i = 0; i < visValues.Length; i++)
{
if (visValues[i] != 0)
{
visValues[i] = (visValues[i] / visValues.Max()) * 255;
}
if (visValues[i] == 0)
{
lY.Add(i);
}
}
if (lX.Count != 0)
{
meanX = lX.Average();
}
else
{
meanX = 0;
}
if (lY.Count != 0)
{
meanY = lY.Average();
}
else
{
meanY = 0;
}
Rectangle r = new Rectangle((int)meanX, (int)meanY, 10, 10);
g.DrawRectangle(new Pen(Color.Aqua), r);
}
return(test);
}
/// <summary>
/// Performs hand detection calculations within the given areas.
/// </summary>
/// <param name="bmp">The camera frame to be processed</param>
/// <param name="areas">A list of rectangles in which the hand detection is to be calculated</param>
/// <returns>A list of coordinates representing the location of each hand</returns>
public static List <Point> GetHandLocations(Bitmap bmp, List <Rectangle> areas)
{
List <Point> hands = new List <Point>();
foreach (Rectangle rect in areas)
{
Bitmap partial = bmp.Clone(rect, bmp.PixelFormat);
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(partial);
VerticalIntensityStatistics vis = new VerticalIntensityStatistics(partial);
Histogram gray = his.Gray;
Histogram GrayY = vis.Gray;
double meanX;
double meanY;
int[] hisValues = (int[])his.Gray.Values.Clone();
int[] visValues = (int[])vis.Gray.Values.Clone();
List <int> lX = new List <int>();
List <int> lY = new List <int>();
for (int i = 0; i < hisValues.Length; i++)
{
if (hisValues[i] != 0)
{
hisValues[i] = (hisValues[i] / hisValues.Max()) * 255;
}
if (hisValues[i] == 0)
{
lX.Add(i + rect.X);
}
}
for (int i = 0; i < visValues.Length; i++)
{
if (visValues[i] != 0)
{
visValues[i] = (visValues[i] / visValues.Max()) * 255;
}
if (visValues[i] == 0)
{
lY.Add(i + rect.Y);
}
}
if (lX.Count != 0)
{
meanX = lX.Average();
}
else
{
meanX = 0;
}
if (lY.Count != 0)
{
meanY = lY.Average();
}
else
{
meanY = 0;
}
hands.Add(new Point((int)meanX, (int)meanY));
}
return(hands);
}
void SelectedCam_NewFrame(object sender, NewFrameEventArgs eventArgs)
{
Bitmap bmp = new Bitmap(100, 100);
Graphics placeholder = Graphics.FromImage(bmp);
placeholder.FillRectangle(Brushes.White, 0, 0, bmp.Width, bmp.Height);
Bitmap image = (Bitmap)eventArgs.Frame.Clone();
Bitmap originalImage = (Bitmap)eventArgs.Frame.Clone();
// set color ranges to keep red-orange
filter.Hue = new IntRange(0, 35);
filter.Saturation = new Range(0.19f, 1);
//filter.Luminance = new Range(0.31f, 255);
// apply the filter
filter.ApplyInPlace(image);
openingFilter.ApplyInPlace(image);
Bitmap greyimage = grayscaleFilter.Apply(image);
thresholdFilter.ApplyInPlace(greyimage);
erosionFilter.Apply(greyimage);
// process binary image
bc.ProcessImage(image);
bc.MinWidth = 50;
bc.MinHeight = 50;
bc.FilterBlobs = true;
bc.ObjectsOrder = ObjectsOrder.Size;
Rectangle[] rects = bc.GetObjectsRectangles();
if (rects.Length > 0)
{
bmp = new Bitmap(rects[0].Width, rects[0].Height);
Graphics g = Graphics.FromImage(bmp);
g.DrawImage(greyimage, 0, 0, rects[0], GraphicsUnit.Pixel);
g.Dispose();
// process blobs
foreach (Rectangle rect in rects)
{
Graphics g1 = Graphics.FromImage(originalImage);
using (Pen pen = new Pen(Color.FromArgb(160, 255, 160), 5))
{
g1.DrawRectangle(pen, rect);
}
g1.Dispose();
}
}
Crop cropFilter = new Crop(new Rectangle(0, (int)(0.15 * bmp.Height), bmp.Width, (int)(0.25 * bmp.Height)));
Bitmap handImage = cropFilter.Apply(bmp);
Bitmap overlay = new Bitmap(handImage.Width, handImage.Height);
using (Graphics g = Graphics.FromImage(overlay))
{
g.FillRectangle(Brushes.White, 0, 0, overlay.Width, overlay.Height);
}
Subtract subfilter = new Subtract(handImage);
Bitmap resultImage = subfilter.Apply(overlay);
HorizontalIntensityStatistics his = new HorizontalIntensityStatistics(handImage);
double palmlimit = 0.4 * handImage.Height;
int[] hisValues = (int[])his.Red.Values.Clone();
for (int i = 0; i < handImage.Width; i++)
{
hisValues[i] = ((double)hisValues[i] / 255 > palmlimit) ? 1 : 0;
}
histogram.Values = his.Red.Values;
histogram1.Values = hisValues;
//display number of fingers
Graphics num = Graphics.FromImage(image);
string text = "0";
if (bmp.Height > 1.5 * bmp.Width)
{
text = string.Format(countfingers(hisValues));
}
else
{
text = "0";
}
Font drawFont = new Font("Courier", 18, FontStyle.Bold);
SolidBrush drawBrush = new SolidBrush(Color.White);
num.DrawString(text, drawFont, drawBrush, new PointF(0, 5));
drawFont.Dispose();
drawBrush.Dispose();
num.Dispose();
// display in picture box
pictureBox1.Image = originalImage;
original.Image = image;
crop.Image = handImage;
}