screenhistostretchgrays.pas

给出了基于神经网络的手写体数字的识别程序

            //这里采用方法二
            Gray := Max(p[3 * x + 2], p[3 * x + 1]);
            Gray := Max(Gray, p[3 * x]);
            p[3 * x + 2] := byte(Gray);
            p[3 * x + 1] := byte(Gray);
            p[3 * x] := byte(Gray);
        end;
    end;
    Bitmap.Assign(Bmp);
    Bmp.Free;

end;

procedure TFormHistoStretchGrays.TwoValueTrackBarChange(Sender: TObject);
begin
  TwoValueFlagLabel.Caption:=IntToStr(128+ TwoValueTrackBar.position);
  UpdateDisplay;
  twovalue2Click(Sender);
end;

procedure TFormHistoStretchGrays.PlateProjectionClick(Sender: TObject);
Var
  DistributionX: array[0..500] of integer;
  DistributionY: array[0..500] of integer;
  CharStart,CharEnd: array[0..15] of integer;
  Bmp1: TBitmap;
  x,y,i,charwidth:Integer;
  ptr1, ptr2: pbytearray;
begin
  Series1.Clear();  Series2.Clear();
  i:=1; charwidth:=1;
    for    X:=0 to 500  do
      DistributionX[X]:=0;
     for    Y:=0 to 500  do
     DistributionX[Y]:=0;
    bmp1:= TBitmap.Create;
   bmp1.Assign(plateimg.Picture.Bitmap);
   bmp1.PixelFormat := pf24bit;
      for    y:=4 to Bmp1.Height-4  do
   begin
   ptr1:=Bmp1.ScanLine[y];
        if ptr1[y*3]=255 then
              DistributionY[y]:=DistributionY[Y]+1;
    for x:=4 to Bmp1.Width-4 do
          begin
         if ptr1[x*3]=255 then
             DistributionX[x]:=DistributionX[x]+1;
               end;
   end;
 for x:=4 to Bmp1.Width-4  do
    begin
    Series1.Add(DistributionX[x],inttostr(x),TColor(clwHITE));
       if ((DistributionX[x]>=3) and (DistributionX[x-1]<3))
       then
          begin
           CharStart[i]:=x;
          end;
      if ((DistributionX[x]>=3) and (DistributionX[x-1]>=3))
      then charwidth:=charwidth+1;
     if ((DistributionX[x]<3) and (DistributionX[x-1]>=3))
     and (charwidth>=2) then //最小的字宽大于2个像素
           begin
            Charend[i]:=x-1; i:=i+1; charwidth:=0;
            end;
    end;
    CharNumLabel.Caption:=inttoStr(i-1);
    CharNumber:=i-1; //字符跳变的次数，如大于5，可能是车牌
    Bmp1.Free;
end;

procedure TFormHistoStretchGrays.PlateTwoValueClick(Sender: TObject);
begin
    PictureTwoValue2(plateimg.Picture.Bitmap,PlateTwoValueTrackBar.Position+128);
end;

procedure TFormHistoStretchGrays.GrayClick(Sender: TObject);
begin
   imageGray(ImageOriginal.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.PlateGrayClick(Sender: TObject);
begin
   imageGray(PlateImg.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.GetPlateColorImageClick(Sender: TObject);
var
   bmp1, bmp2: Tbitmap;
   // 临时位图
   p1: pByteArray;
 //  c,x,y,xmin,xmax,ymin,ymax: integer;
   PlateRect1,PlateRect2:trect;
   TheRect: TRect;
begin
 //  plateImg.Picture.Assign(nil);
   self.DoubleBuffered := true;
   //采用双缓冲模式
   bmp1 := Tbitmap.Create;
   bmp2 := Tbitmap.Create;
   //Create  bmp1,bmp2
  bmp1.Assign(OroginalColorImage.Picture.Bitmap);
  bmp1.PixelFormat := pf24bit;
   //设置位图格式
  bmp2.Assign(plateimg.Picture.bitmap);
  bmp2.PixelFormat := pf24bit;
      PlateRect1:=rect(Platexmin,Plateymin,Platexmax,Plateymax);
      PlateRect2:=rect(0,0,Platexmax-Platexmin,Plateymax-Plateymin);
      plateimg.Width:=platexmax-platexmin;
      plateimg.Height:=plateymax-plateymin;
      plateimg.Canvas.copyrect(PlateRect2,ImageOriginal.canvas,PlateRect1);
   bmp1.Free;
   bmp2.Free;
end;

procedure TFormHistoStretchGrays.plateimgMouseMove(Sender: TObject;
  Shift: TShiftState; X, Y: Integer);
begin
      xLabel.caption:=inttoStr(x);
      yLabel.caption:=inttoStr(y);
   //   grayvalueLabel.caption:= inttostr( GetRvalue(plateimg.Canvas.Pixels[x,y] ));
end;

procedure TFormHistoStretchGrays.PlateImageFiletClick(Sender: TObject);
begin
      ImageFilet(plateimg.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.GrayImageFiletClick(Sender: TObject);
begin
  ImageFilet(ImageHistoStretched.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.PlatePositionFurtherCertificationClick(
  Sender: TObject);
begin
    CharNumber:=0;
   // GetPlateColorImageClick(Sender);
  PlateGrayStrentchClick(Sender);
      OptialTwoValueClick(Sender);
      PLATETwoValueTrackBar.Position:= optialT-128;
   //   PlateTwoValueTrackBarChange(Sender);
      PlateTwoValueClick(Sender);
     PlateProjectionClick(Sender);
     if (CharNumber>=5) then MessageDlg('车排位置正确',
          mtConfirmation, [mbYes, mbNo],0) else
    MessageDlg('不是真的车排位置,继续搜索',
        mtConfirmation, [mbYes, mbNo],0);

end;

procedure TFormHistoStretchGrays.OptiumTwoValueClick(BitMap:TBitmap);
var
   X, Y,GraySumInImage,MeanGrayInImage: integer;
   P: pByteArray;
   c,t1,sqrtr1mr2:double;
   newbmp: TBitmap;
   gray: byte;
   GrayDistribution: array[0..256] of integer;
begin
   imageGray(PlateImg.Picture.Bitmap);//首先将车牌普通方法灰度化
   newbmp := TBitmap.Create;
   newbmp.PixelFormat := pf24bit;
   newbmp.Assign(bitmap);
   for Y := 0 to bitmap.Height - 1 do
   begin
      P := newbmp.ScanLine[Y];
      for X := 0 to bitmap.Width - 1 do
      begin
      GraySumInImage:=p[3*x]+GraySumInImage;
      GrayDistribution[p[3*x]]:=GrayDistribution[p[3*x]]+1;
      end;
   end;
     MeanGrayInImage:=Round(GraySumInImage/(bitmap.Height*bitmap.Width));
     MeanGrayValue.Caption:=inttostr(MeanGrayInImage);
     sqrtr1mr2:=0.610;
     c:=sqrtr1mr2*(255-MeanGrayInImage);
     t1:=MeanGrayInImage+sqrtr1mr2*c;
     MeanGrayValue.Caption:=inttostr(MeanGrayInImage);
     bestGraylabel.Caption:=inttostr(round(t1));
     optialT:=round(T1);
     bitmap.Assign(newbmp);
     newbmp.free;
end;

procedure TFormHistoStretchGrays.OptialTwoValueClick(Sender: TObject);
begin
    bestGrayLabel.Caption:='';
    OptiumTwoValueClick(plateimg.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.PlateGrayDistributionClick(
  Sender: TObject);
VAR
  GrayDistribution: array[0..256] of integer;
  Bmp1: TBitmap;
  x,y,i:Integer;
  ptr1, ptr2: pbytearray;
begin
 Series2.Clear();  
  for    i:=0 to 256  do
         begin
   GrayDistribution[i]:=0;
          END;
   bmp1:= TBitmap.Create;
   bmp1.Assign(plateimg.Picture.Bitmap);
  // bmp1.PixelFormat := pf24bit;
      for    y:=0 to Bmp1.Height-1  do
   begin
           ptr1:=Bmp1.ScanLine[y];
      for x:=0 to Bmp1.Width-1 do
          begin
       GrayDistribution[ptr1[3*x]]:=GrayDistribution[ptr1[3*x]]+1;
          end;
   end;
       for i:=0 to 255  do
      begin
       Series2.Add(GrayDistribution[i],inttostr(i),TColor(clred));
               end;
      // GrayMaxLabel.Caption:=inttostr(GrayDistribution[200]);
       Bmp1.Free;
end;

procedure TFormHistoStretchGrays.plateimgClick(Sender: TObject);
begin
//     plateimg.Picture.LoadFromFile('001.bmp');
end;


procedure TFormHistoStretchGrays.PlateTwoValueTrackBarChange(
  Sender: TObject);
begin
//    plateimg.Picture.Bitmap.Assign(ImageHistoStretched.Picture.Bitmap);
//   plateimg.Picture.Assign(platecolorimg.Picture.Bitmap);
  GetPlateColorImageClick(Sender);
  PlateGrayClick(Sender);
  PlateTwoValueLabel.Caption:=IntToStr(128+ PlateTwoValueTrackBar.position);
  PlateTwoValueClick(Sender);
end;

procedure TFormHistoStretchGrays.N4Click(Sender: TObject);
begin
   plateimg.Picture.Bitmap.Assign(ImageHistoStretched.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.OtsuAlgorithmClick(Sender: TObject;BitMap:TBitmap);
var
  row, col:integer;
  i, T:integer;
  n,P, Sum_Pi,Sum_Pi_i: array[0..256] of double;
  W1, W2, U1, U2, sumpixel:Double;
  Sigma_1_square, Sigma_2_square, Sigma_w_square:double;
  MinVariance :double;
   ptr:pbytearray;
   T_optimal:integer;
begin
  MinVariance :=  1.7e+308 ;
  // 計算影像的總像素數
  sumpixel := BitMap.Width * BitMap.Height;
  // 統計影像中灰階值為i的像素數
  for i := 0 to  256 do
    n[i] := 0;
  for row := 0 to BitMap.Height-1 do
  begin
        ptr := BitMap.ScanLine[row];
        for col := 0 to Bitmap.Width-1 do
         n[ ptr[col] ]:=n[ ptr[col] ]+1;
  end;
  // 計算影像中灰階值為i的像素所出現的機率
 for i := 0 to 255 do
    P[i] := n[i] /sumpixel;
     // 分別計算門檻值為T時，Sum_Pi和Sum_Pi_i
  Sum_Pi[0]   := P[0];
  Sum_Pi_i[0] := 0;
  for i := 1 to 255 do
  begin
    Sum_Pi[i]   := Sum_Pi[i-1] + P[i];
    Sum_Pi_i[i] := Sum_Pi_i[i-1] + P[i] * i;
  end ; // 檢查所有的灰階值，使C1和C2的變異數和為最小時
  // 即為所求的最佳門檻值
  for T := 1 to 254 do
    begin
    W1:= Sum_Pi[T];
    // 加上最小值檢查，避免除數為零
    if (Abs(W1) < 1e-9) then
       W1:= 1e-9;
       W2 := 1 - W1;
    // 加上最小值檢查，避免除數為零
    if (Abs(W2) < 1e-9) then W2 := 1e-9;
       U1:= Sum_Pi_i[T] / W1;
    U2 := (Sum_Pi_i[255] - Sum_Pi_i[T]) / W2;
       Sigma_1_square:= 0;
    for i:= 0 to T do
    Sigma_1_square :=Sigma_1_square+(i - U1) * ( i - U1) * P[i];
    Sigma_1_square := Sigma_1_square / W1;
    Sigma_2_square := 0;                        
         for i := T+1 to 255 do
           begin
            Sigma_2_square:= Sigma_2_square+(i- U2) * (i - U2) * P[i];
            end ;
    Sigma_2_square := Sigma_2_square / W2;
       Sigma_w_square := W1 * Sigma_1_square + W2 * Sigma_2_square;
       if(Sigma_w_square < MinVariance)  then
          begin
            MinVariance := Sigma_w_square;
            optialT:=T;
          end;
 end;
 // 回傳最佳門檻值
 bestGrayLabel.Caption:=inttostr(optialT);
   end;

procedure TFormHistoStretchGrays.Otsu(Sender: TObject);
begin
  OtsuAlgorithmClick(Sender,plateimg.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.Otisu1Click(Sender: TObject);
begin
  OtsuAlgorithmClick(Sender,ImageHistoStretched.Picture.Bitmap);
  TwoValueTrackBar.Position:=optialT-128;
  PictureTwoValue(ImageHistoStretched.Picture.Bitmap,TwoValueTrackBar.Position+128);
end;

procedure TFormHistoStretchGrays.DFDS1Click(Sender: TObject);
begin
   UpdateDisplay;
end;

procedure TFormHistoStretchGrays.CarGrayStreenchClick(Sender: TObject);
begin
   GetGrayParam(ImageHistoStretched.Picture.Bitmap);
   GrayStretch(ImageHistoStretched.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.PlateGrayStrentchClick(Sender: TObject);
begin
  GetGrayParam(plateimg.Picture.Bitmap);
  GrayStretch(plateimg.Picture.Bitmap);
end;

procedure TFormHistoStretchGrays.showgraystaticsClick(Sender: TObject);
  var
    StretchedHistogram:  THistogram;
     // Update Display of Histograms.  Some work will be redone below to create
    // optimal Histostretch parameters.
begin
//  StretchedHistogram:= THistogram.Create;
  //ShowHistogram(StretchedHistogram, ImageHistogramStretched,LabelStretchedStats);
 // StretchedHistogram.Free;
end;

procedure TFormHistoStretchGrays.GetBlueColorPlateClick(Sender: TObject);

var
   bmp: TBITMAP;
   x, y, ScanlineBytes: integer;
   p: prgbtriplearray;
   RVALUE, bvalue, gvalue: integer;
   hVALUE, sVALUE, lVALUE: integer;
begin
   self.DoubleBuffered := true;
   //设置双缓冲
   bmp := TBITMAP.Create;
   bmp.Assign(OroginalColorImage.Picture.Bitmap);
   //加载位图
   bmp.PixelFormat := pf24bit;
   //指定为24位
   p := bmp.ScanLine[0];
   ScanlineBytes := integer(bmp.ScanLine[1]) - integer(bmp.ScanLine[0]);
   //获取两行间距，此法只需执行Scanline两次，速度快，是优化的
   for y := 0 to bmp.Height - 1 do
      begin
         for x := 0 to bmp.Width - 1 do
            begin //获取RGB的三个分量值，并进行赋值
               RVALUE := p[x].rgbtRed;
               gVALUE := p[x].rgbtGreen;
               bVALUE := p[x].rgbtBlue;
               // 调用前面的RGB转HSL过程，获取HSL三个分量值
               RGBtoHSL(RVALUE, gVALUE, bVALUE, hVALUE, sVALUE, lVALUE);
               lVALUE := min(100, lVALUE);
               //调用前面的HSL空间转RGB颜色空间的过程，获得RGB三个分量
              if (hVALUE<=170) or (hVALUE>=240) then hVALUE:=360;
               HSLtorgb(hVALUE, sVALUE, lVALUE, rVALUE, gVALUE, bVALUE);
               p[x].rgbtRed := RVALUE;
               p[x].rgbtGreen := gVALUE;
               p[x].rgbtBlue := bVALUE;
            end;
         inc(integer(p), ScanlineBytes);
         //指针递增
      end;
   ImageHistoStretched.Picture.Bitmap.Assign(bmp);
   Bmp.Free;
end;
procedure TFormHistoStretchGrays.HSLtoRGB(H, S, L: Integer; var R, G, B: Integer);
//hsl颜色空间到rgb空间的转换
var //类似于返回多个值的函数
   Sat, Lum: Double;
begin
   R := 0;
   G := 0;
   B := 0;
   if (H < 360) and (H >= 0) and (S <= 100) and (S >= 0) and (L <= 100) and (L
      >=
      0) then
      begin
         if H <= 60 then
            begin
               R := 255;
               G := Round((255 / 60) * H);
               B := 0;
            end
         else if H <= 120 then
            begin