C#验证码识别类完整实例

using System;using System.Collections.Generic;using System.Linq;using System.Text;using System.Drawing;using System.Drawing.Imaging;using System.Runtime.InteropServices;namespace 验证码处理{ class VerifyCode {  public Bitmap bmpobj;  public VerifyCode(Bitmap pic)  {   bmpobj = new Bitmap(pic);  //转换为Format32bppRgb  }  /// <summary>  /// 根据RGB，计算灰度值  /// </summary>  /// <param name="posClr">Color值</param>  /// <returns>灰度值，整型</returns>  private int GetGrayNumColor(System.Drawing.Color posClr)  {   return (posClr.R * 19595 + posClr.G * 38469 + posClr.B * 7472) >> 16;  }  /// <summary>  /// 灰度转换,逐点方式  /// </summary>  public void GrayByPixels()  {   for (int i = 0; i < bmpobj.Height; i++)   {    for (int j = 0; j < bmpobj.Width; j++)    {     int tmpValue = GetGrayNumColor(bmpobj.GetPixel(j, i));     bmpobj.SetPixel(j, i, Color.FromArgb(tmpValue, tmpValue, tmpValue));    }   }  }  /// <summary>  /// 去图形边框  /// </summary>  /// <param name="borderWidth"></param>  public void ClearPicBorder(int borderWidth)  {   for (int i = 0; i < bmpobj.Height; i++)   {    for (int j = 0; j < bmpobj.Width; j++)    {     if (i < borderWidth || j < borderWidth || j > bmpobj.Width - 1 - borderWidth || i > bmpobj.Height - 1 - borderWidth)      bmpobj.SetPixel(j, i, Color.FromArgb(255, 255, 255));    }   }  }  /// <summary>  /// 灰度转换,逐行方式  /// </summary>  public void GrayByLine()  {   Rectangle rec = new Rectangle(0, 0, bmpobj.Width, bmpobj.Height);   BitmapData bmpData = bmpobj.LockBits(rec, ImageLockMode.ReadWrite, bmpobj.PixelFormat);// PixelFormat.Format32bppPArgb);   //  bmpData.PixelFormat = PixelFormat.Format24bppRgb;   IntPtr scan0 = bmpData.Scan0;   int len = bmpobj.Width * bmpobj.Height;   int[] pixels = new int[len];   Marshal.Copy(scan0, pixels, 0, len);   //对图片进行处理   int GrayValue = 0;   for (int i = 0; i < len; i++)   {    GrayValue = GetGrayNumColor(Color.FromArgb(pixels[i]));    pixels[i] = (byte)(Color.FromArgb(GrayValue, GrayValue, GrayValue)).ToArgb();  //Color转byte   }   bmpobj.UnlockBits(bmpData);   ////输出   //GCHandle gch = GCHandle.Alloc(pixels, GCHandleType.Pinned);   //bmpOutput = new Bitmap(bmpobj.Width, bmpobj.Height, bmpData.Stride, bmpData.PixelFormat, gch.AddrOfPinnedObject());   //gch.Free();  }  /// <summary>  /// 得到有效图形并调整为可平均分割的大小  /// </summary>  /// <param name="dgGrayValue">灰度背景分界值</param>  /// <param name="CharsCount">有效字符数</param>  /// <returns></returns>  public void GetPicValidByValue(int dgGrayValue, int CharsCount)  {   int posx1 = bmpobj.Width; int posy1 = bmpobj.Height;   int posx2 = 0; int posy2 = 0;   for (int i = 0; i < bmpobj.Height; i++)  //找有效区   {    for (int j = 0; j < bmpobj.Width; j++)    {     int pixelValue = bmpobj.GetPixel(j, i).R;     if (pixelValue < dgGrayValue)  //根据灰度值     {      if (posx1 > j) posx1 = j;      if (posy1 > i) posy1 = i;       if (posx2 < j) posx2 = j;      if (posy2 < i) posy2 = i;     };    };   };   // 确保能整除   int Span = CharsCount - (posx2 - posx1 + 1) % CharsCount; //可整除的差额数   if (Span < CharsCount)   {    int leftSpan = Span / 2;  //分配到左边的空列 ，如span为单数,则右边比左边大1    if (posx1 > leftSpan)     posx1 = posx1 - leftSpan;    if (posx2 + Span - leftSpan < bmpobj.Width)     posx2 = posx2 + Span - leftSpan;   }   //复制新图   Rectangle cloneRect = new Rectangle(posx1, posy1, posx2 - posx1 + 1, posy2 - posy1 + 1);   bmpobj = bmpobj.Clone(cloneRect, bmpobj.PixelFormat);  }  /// <summary>  /// 得到有效图形,图形为类变量  /// </summary>  /// <param name="dgGrayValue">灰度背景分界值</param>  /// <param name="CharsCount">有效字符数</param>  /// <returns></returns>  public void GetPicValidByValue(int dgGrayValue)  {   int posx1 = bmpobj.Width; int posy1 = bmpobj.Height;   int posx2 = 0; int posy2 = 0;   for (int i = 0; i < bmpobj.Height; i++)  //找有效区   {    for (int j = 0; j < bmpobj.Width; j++)    {     int pixelValue = bmpobj.GetPixel(j, i).R;     if (pixelValue < dgGrayValue)  //根据灰度值     {      if (posx1 > j) posx1 = j;      if (posy1 > i) posy1 = i;       if (posx2 < j) posx2 = j;      if (posy2 < i) posy2 = i;     };    };   };   //复制新图   Rectangle cloneRect = new Rectangle(posx1, posy1, posx2 - posx1 + 1, posy2 - posy1 + 1);   bmpobj = bmpobj.Clone(cloneRect, bmpobj.PixelFormat);  }  /// <summary>  /// 得到有效图形,图形由外面传入  /// </summary>  /// <param name="dgGrayValue">灰度背景分界值</param>  /// <param name="CharsCount">有效字符数</param>  /// <returns></returns>  public Bitmap GetPicValidByValue(Bitmap singlepic, int dgGrayValue)  {   int posx1 = singlepic.Width; int posy1 = singlepic.Height;   int posx2 = 0; int posy2 = 0;   for (int i = 0; i < singlepic.Height; i++)  //找有效区   {    for (int j = 0; j < singlepic.Width; j++)    {     int pixelValue = singlepic.GetPixel(j, i).R;     if (pixelValue < dgGrayValue)  //根据灰度值     {      if (posx1 > j) posx1 = j;      if (posy1 > i) posy1 = i;       if (posx2 < j) posx2 = j;      if (posy2 < i) posy2 = i;     };    };   };   //复制新图   Rectangle cloneRect = new Rectangle(posx1, posy1, posx2 - posx1 + 1, posy2 - posy1 + 1);   return singlepic.Clone(cloneRect, singlepic.PixelFormat);  }  /// <summary>  /// 平均分割图片  /// </summary>  /// <param name="RowNum">水平上分割数</param>  /// <param name="ColNum">垂直上分割数</param>  /// <returns>分割好的图片数组</returns>  public Bitmap [] GetSplitPics(int RowNum,int ColNum)  {   if (RowNum == 0 || ColNum == 0)    return null;   int singW = bmpobj.Width / RowNum;   int singH = bmpobj.Height / ColNum;   Bitmap [] PicArray=new Bitmap[RowNum*ColNum];   Rectangle cloneRect;   for (int i = 0; i < ColNum; i++)  //找有效区   {    for (int j = 0; j < RowNum; j++)    {     cloneRect = new Rectangle(j*singW, i*singH, singW , singH);     PicArray[i*RowNum+j]=bmpobj.Clone(cloneRect, bmpobj.PixelFormat);//复制小块图    }   }   return PicArray;  }  /// <summary>  /// 返回灰度图片的点阵描述字串，1表示灰点，0表示背景  /// </summary>  /// <param name="singlepic">灰度图</param>  /// <param name="dgGrayValue">背前景灰色界限</param>  /// <returns></returns>  public string GetSingleBmpCode(Bitmap singlepic, int dgGrayValue)  {   Color piexl;   string code = "";   for (int posy = 0; posy < singlepic.Height; posy++)    for (int posx = 0; posx < singlepic.Width; posx++)    {     piexl = singlepic.GetPixel(posx, posy);     if (piexl.R < dgGrayValue)  // Color.Black )      code = code + "1";     else      code = code + "0";    }   return code;  }  /// <summary>  /// 得到灰度图像前景背景的临界值 最大类间方差法  /// </summary>  /// <returns>前景背景的临界值</returns>  public int GetDgGrayValue()  {   int[] pixelNum = new int[256];   //图象直方图，共256个点   int n, n1, n2;   int total;        //total为总和，累计值   double m1, m2, sum, csum, fmax, sb;  //sb为类间方差，fmax存储最大方差值   int k, t, q;   int threshValue = 1;      // 阈值   //生成直方图   for (int i = 0; i < bmpobj.Width; i++)   {    for (int j = 0; j < bmpobj.Height; j++)    {     //返回各个点的颜色，以RGB表示     pixelNum[bmpobj.GetPixel(i, j).R]++;    //相应的直方图加1    }   }   //直方图平滑化   for (k = 0; k <= 255; k++)   {    total = 0;    for (t = -2; t <= 2; t++)    //与附近2个灰度做平滑化，t值应取较小的值    {     q = k + t;     if (q < 0)      //越界处理      q = 0;     if (q > 255)      q = 255;     total = total + pixelNum[q];  //total为总和，累计值    }    pixelNum[k] = (int)((float)total / 5.0 + 0.5);  //平滑化，左边2个+中间1个+右边2个灰度，共5个，所以总和除以5，后面加0.5是用修正值   }   //求阈值   sum = csum = 0.0;   n = 0;   //计算总的图象的点数和质量矩，为后面的计算做准备   for (k = 0; k <= 255; k++)   {    sum += (double)k * (double)pixelNum[k];  //x*f(x)质量矩，也就是每个灰度的值乘以其点数（归一化后为概率），sum为其总和    n += pixelNum[k];      //n为图象总的点数，归一化后就是累积概率   }   fmax = -1.0;       //类间方差sb不可能为负，所以fmax初始值为-1不影响计算的进行   n1 = 0;   for (k = 0; k < 256; k++)     //对每个灰度（从0到255）计算一次分割后的类间方差sb   {    n1 += pixelNum[k];     //n1为在当前阈值遍前景图象的点数    if (n1 == 0) { continue; }    //没有分出前景后景    n2 = n - n1;       //n2为背景图象的点数    if (n2 == 0) { break; }    //n2为0表示全部都是后景图象，与n1=0情况类似，之后的遍历不可能使前景点数增加，所以此时可以退出循环    csum += (double)k * pixelNum[k];  //前景的“灰度的值*其点数”的总和    m1 = csum / n1;      //m1为前景的平均灰度    m2 = (sum - csum) / n2;    //m2为背景的平均灰度    sb = (double)n1 * (double)n2 * (m1 - m2) * (m1 - m2); //sb为类间方差    if (sb > fmax)     //如果算出的类间方差大于前一次算出的类间方差    {     fmax = sb;      //fmax始终为最大类间方差（otsu）     threshValue = k;    //取最大类间方差时对应的灰度的k就是最佳阈值    }   }   return threshValue;  }  /// <summary>  /// 去掉杂点（适合杂点/杂线粗为1）  /// </summary>  /// <param name="dgGrayValue">背前景灰色界限</param>  /// <returns></returns>  public void ClearNoise(int dgGrayValue, int MaxNearPoints)  {   Color piexl;   int nearDots = 0;   //逐点判断   for (int i = 0; i < bmpobj.Width; i++)    for (int j = 0; j < bmpobj.Height; j++)    {     piexl = bmpobj.GetPixel(i, j);     if (piexl.R < dgGrayValue)     {      nearDots = 0;      //判断周围8个点是否全为空      if (i == 0 || i == bmpobj.Width - 1 || j == 0 || j == bmpobj.Height - 1) //边框全去掉      {       bmpobj.SetPixel(i, j, Color.FromArgb(255, 255, 255));      }      else      {       if (bmpobj.GetPixel(i - 1, j - 1).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i, j - 1).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i + 1, j - 1).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i - 1, j).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i + 1, j).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i - 1, j + 1).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i, j + 1).R < dgGrayValue) nearDots++;       if (bmpobj.GetPixel(i + 1, j + 1).R < dgGrayValue) nearDots++;      }      if (nearDots < MaxNearPoints)       bmpobj.SetPixel(i, j, Color.FromArgb(255, 255, 255)); //去掉单点 && 粗细小3邻边点     }     else //背景      bmpobj.SetPixel(i, j, Color.FromArgb(255, 255, 255));    }  }  /// <summary>  /// 3×3中值滤波除杂  /// </summary>  /// <param name="dgGrayValue"></param>  public void ClearNoise(int dgGrayValue)  {   int x, y;   byte[] p = new byte[9]; //最小处理窗口3*3   byte s;   //byte[] lpTemp=new BYTE[nByteWidth*nHeight];   int i, j;   //--!!!!!!!!!!!!!!下面开始窗口为3×3中值滤波!!!!!!!!!!!!!!!!   for (y = 1; y < bmpobj.Height - 1; y++) //--第一行和最后一行无法取窗口   {    for (x = 1; x < bmpobj.Width - 1; x++)    {     //取9个点的值     p[0] = bmpobj.GetPixel(x - 1, y - 1).R;     p[1] = bmpobj.GetPixel(x, y - 1).R;     p[2] = bmpobj.GetPixel(x + 1, y - 1).R;     p[3] = bmpobj.GetPixel(x - 1, y).R;     p[4] = bmpobj.GetPixel(x, y).R;     p[5] = bmpobj.GetPixel(x + 1, y).R;     p[6] = bmpobj.GetPixel(x - 1, y + 1).R;     p[7] = bmpobj.GetPixel(x, y + 1).R;     p[8] = bmpobj.GetPixel(x + 1, y + 1).R;     //计算中值     for (j = 0; j < 5; j++)     {      for (i = j + 1; i < 9; i++)      {       if (p[j] > p[i])       {        s = p[j];        p[j] = p[i];        p[i] = s;       }      }     }     //  if (bmpobj.GetPixel(x, y).R < dgGrayValue)     bmpobj.SetPixel(x, y, Color.FromArgb(p[4], p[4], p[4]));  //给有效值付中值    }   }  }  /// <summary>  /// 该函数用于对图像进行腐蚀运算。结构元素为水平方向或垂直方向的三个点，  /// 中间点位于原点；或者由用户自己定义3×3的结构元素。  /// </summary>  /// <param name="dgGrayValue">前后景临界值</param>  /// <param name="nMode">腐蚀方式：0表示水平方向，1垂直方向，2自定义结构元素。</param>  /// <param name="structure"> 自定义的3×3结构元素</param>  public void ErosionPic(int dgGrayValue, int nMode, bool[,] structure)  {   int lWidth = bmpobj.Width;   int lHeight = bmpobj.Height;   Bitmap newBmp = new Bitmap(lWidth, lHeight);   int i, j, n, m;    //循环变量   if (nMode == 0)   {    //使用水平方向的结构元素进行腐蚀    // 由于使用1×3的结构元素，为防止越界，所以不处理最左边和最右边    // 的两列像素    for (j = 0; j < lHeight; j++)    {     for (i = 1; i < lWidth - 1; i++)     {      //目标图像中的当前点先赋成黑色      newBmp.SetPixel(i, j, Color.Black);       //如果源图像中当前点自身或者左右有一个点不是黑色，      //则将目标图像中的当前点赋成白色      if (bmpobj.GetPixel(i - 1, j).R > dgGrayValue ||       bmpobj.GetPixel(i, j).R > dgGrayValue ||       bmpobj.GetPixel(i + 1, j).R > dgGrayValue)       newBmp.SetPixel(i, j, Color.White);     }    }   }   else if (nMode == 1)   {    //使用垂真方向的结构元素进行腐蚀    // 由于使用3×1的结构元素，为防止越界，所以不处理最上边和最下边    // 的两行像素    for (j = 1; j < lHeight - 1; j++)    {     for (i = 0; i < lWidth; i++)     {      //目标图像中的当前点先赋成黑色      newBmp.SetPixel(i, j, Color.Black);      //如果源图像中当前点自身或者左右有一个点不是黑色，      //则将目标图像中的当前点赋成白色      if (bmpobj.GetPixel(i, j - 1).R > dgGrayValue ||       bmpobj.GetPixel(i, j).R > dgGrayValue ||       bmpobj.GetPixel(i, j + 1).R > dgGrayValue)       newBmp.SetPixel(i, j, Color.White);     }    }   }   else   {    if (structure.Length != 9) //检查自定义结构     return;    //使用自定义的结构元素进行腐蚀    // 由于使用3×3的结构元素，为防止越界，所以不处理最左边和最右边    // 的两列像素和最上边和最下边的两列像素    for (j = 1; j < lHeight - 1; j++)    {     for (i = 1; i < lWidth - 1; i++)     {      //目标图像中的当前点先赋成黑色      newBmp.SetPixel(i, j, Color.Black);      //如果原图像中对应结构元素中为黑色的那些点中有一个不是黑色，      //则将目标图像中的当前点赋成白色      for (m = 0; m < 3; m++)      {       for (n = 0; n < 3; n++)       {        if (!structure[m, n])         continue;        if (bmpobj.GetPixel(i + m - 1, j + n - 1).R > dgGrayValue)        {         newBmp.SetPixel(i, j, Color.White);         break;        }       }      }     }    }   }   bmpobj = newBmp;  }  /// <summary>  /// 该函数用于对图像进行细化运算。要求目标图像为灰度图像  /// </summary>  /// <param name="dgGrayValue"></param>  public void ThiningPic(int dgGrayValue)  {   int lWidth = bmpobj.Width;   int lHeight = bmpobj.Height;   // Bitmap newBmp = new Bitmap(lWidth, lHeight);   bool bModified;    //脏标记     int i, j, n, m;    //循环变量   //四个条件   bool bCondition1;   bool bCondition2;   bool bCondition3;   bool bCondition4;   int nCount;  //计数器     int[,] neighbour = new int[5, 5];  //5×5相邻区域像素值   bModified = true;   while (bModified)   {    bModified = false;    //由于使用5×5的结构元素，为防止越界，所以不处理外围的几行和几列像素    for (j = 2; j < lHeight - 2; j++)    {     for (i = 2; i < lWidth - 2; i++)     {      bCondition1 = false;      bCondition2 = false;      bCondition3 = false;      bCondition4 = false;      if (bmpobj.GetPixel(i, j).R > dgGrayValue)      {       if (bmpobj.GetPixel(i, j).R < 255)        bmpobj.SetPixel(i, j, Color.White);       continue;      }      //获得当前点相邻的5×5区域内像素值，白色用0代表，黑色用1代表      for (m = 0; m < 5; m++)      {       for (n = 0; n < 5; n++)       {        neighbour[m, n] = bmpobj.GetPixel(i + m - 2, j + n - 2).R < dgGrayValue ? 1 : 0;       }      }      //逐个判断条件。      //判断2<=NZ(P1)<=6      nCount = neighbour[1, 1] + neighbour[1, 2] + neighbour[1, 3]        + neighbour[2, 1] + neighbour[2, 3] +        +neighbour[3, 1] + neighbour[3, 2] + neighbour[3, 3];      if (nCount >= 2 && nCount <= 6)      {       bCondition1 = true;      }      //判断Z0(P1)=1      nCount = 0;      if (neighbour[1, 2] == 0 && neighbour[1, 1] == 1)       nCount++;      if (neighbour[1, 1] == 0 && neighbour[2, 1] == 1)       nCount++;      if (neighbour[2, 1] == 0 && neighbour[3, 1] == 1)       nCount++;      if (neighbour[3, 1] == 0 && neighbour[3, 2] == 1)       nCount++;      if (neighbour[3, 2] == 0 && neighbour[3, 3] == 1)       nCount++;      if (neighbour[3, 3] == 0 && neighbour[2, 3] == 1)       nCount++;      if (neighbour[2, 3] == 0 && neighbour[1, 3] == 1)       nCount++;      if (neighbour[1, 3] == 0 && neighbour[1, 2] == 1)       nCount++;      if (nCount == 1)       bCondition2 = true;      //判断P2*P4*P8=0 or Z0(p2)!=1      if (neighbour[1, 2] * neighbour[2, 1] * neighbour[2, 3] == 0)      {       bCondition3 = true;      }      else      {       nCount = 0;       if (neighbour[0, 2] == 0 && neighbour[0, 1] == 1)        nCount++;       if (neighbour[0, 1] == 0 && neighbour[1, 1] == 1)        nCount++;       if (neighbour[1, 1] == 0 && neighbour[2, 1] == 1)        nCount++;       if (neighbour[2, 1] == 0 && neighbour[2, 2] == 1)        nCount++;       if (neighbour[2, 2] == 0 && neighbour[2, 3] == 1)        nCount++;       if (neighbour[2, 3] == 0 && neighbour[1, 3] == 1)        nCount++;       if (neighbour[1, 3] == 0 && neighbour[0, 3] == 1)        nCount++;       if (neighbour[0, 3] == 0 && neighbour[0, 2] == 1)        nCount++;       if (nCount != 1)        bCondition3 = true;      }      //判断P2*P4*P6=0 or Z0(p4)!=1      if (neighbour[1, 2] * neighbour[2, 1] * neighbour[3, 2] == 0)      {       bCondition4 = true;      }      else      {       nCount = 0;       if (neighbour[1, 1] == 0 && neighbour[1, 0] == 1)        nCount++;       if (neighbour[1, 0] == 0 && neighbour[2, 0] == 1)        nCount++;       if (neighbour[2, 0] == 0 && neighbour[3, 0] == 1)        nCount++;       if (neighbour[3, 0] == 0 && neighbour[3, 1] == 1)        nCount++;       if (neighbour[3, 1] == 0 && neighbour[3, 2] == 1)        nCount++;       if (neighbour[3, 2] == 0 && neighbour[2, 2] == 1)        nCount++;       if (neighbour[2, 2] == 0 && neighbour[1, 2] == 1)        nCount++;       if (neighbour[1, 2] == 0 && neighbour[1, 1] == 1)        nCount++;       if (nCount != 1)        bCondition4 = true;      }      if (bCondition1 && bCondition2 && bCondition3 && bCondition4)      {       bmpobj.SetPixel(i, j, Color.White);       bModified = true;      }      else      {       bmpobj.SetPixel(i, j, Color.Black);      }     }    }   }   // 复制细化后的图像   //  bmpobj = newBmp;  }  /// <summary>  /// 锐化要启用不安全代码编译  /// </summary>  /// <param name="val">锐化程度。取值[0,1]。值越大锐化程度越高</param>  /// <returns>锐化后的图像</returns>  public void Sharpen(float val)  {   int w = bmpobj.Width;   int h = bmpobj.Height;   Bitmap bmpRtn = new Bitmap(w, h, PixelFormat.Format24bppRgb);   BitmapData srcData = bmpobj.LockBits(new Rectangle(0, 0, w, h), ImageLockMode.ReadOnly, PixelFormat.Format24bppRgb);   BitmapData dstData = bmpRtn.LockBits(new Rectangle(0, 0, w, h), ImageLockMode.WriteOnly, PixelFormat.Format24bppRgb);   unsafe   {    byte* pIn = (byte*)srcData.Scan0.ToPointer();    byte* pOut = (byte*)dstData.Scan0.ToPointer();    int stride = srcData.Stride;    byte* p;    for (int y = 0; y < h; y++)    {     for (int x = 0; x < w; x++)     {      //取周围9点的值。位于边缘上的点不做改变。      if (x == 0 || x == w - 1 || y == 0 || y == h - 1)      {       //不做       pOut[0] = pIn[0];       pOut[1] = pIn[1];       pOut[2] = pIn[2];      }      else      {       int r1, r2, r3, r4, r5, r6, r7, r8, r0;       int g1, g2, g3, g4, g5, g6, g7, g8, g0;       int b1, b2, b3, b4, b5, b6, b7, b8, b0;       float vR, vG, vB;       //左上       p = pIn - stride - 3;       r1 = p[2];       g1 = p[1];       b1 = p[0];       //正上       p = pIn - stride;       r2 = p[2];       g2 = p[1];       b2 = p[0];       //右上       p = pIn - stride + 3;       r3 = p[2];       g3 = p[1];       b3 = p[0];       //左侧       p = pIn - 3;       r4 = p[2];       g4 = p[1];       b4 = p[0];       //右侧       p = pIn + 3;       r5 = p[2];       g5 = p[1];       b5 = p[0];       //右下       p = pIn + stride - 3;       r6 = p[2];       g6 = p[1];       b6 = p[0];       //正下       p = pIn + stride;       r7 = p[2];       g7 = p[1];       b7 = p[0];       //右下       p = pIn + stride + 3;       r8 = p[2];       g8 = p[1];       b8 = p[0];       //自己       p = pIn;       r0 = p[2];       g0 = p[1];       b0 = p[0];       vR = (float)r0 - (float)(r1 + r2 + r3 + r4 + r5 + r6 + r7 + r8) / 8;       vG = (float)g0 - (float)(g1 + g2 + g3 + g4 + g5 + g6 + g7 + g8) / 8;       vB = (float)b0 - (float)(b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8) / 8;       vR = r0 + vR * val;       vG = g0 + vG * val;       vB = b0 + vB * val;       if (vR > 0)       {        vR = Math.Min(255, vR);       }       else       {        vR = Math.Max(0, vR);       }       if (vG > 0)       {        vG = Math.Min(255, vG);       }       else       {        vG = Math.Max(0, vG);       }       if (vB > 0)       {        vB = Math.Min(255, vB);       }       else       {        vB = Math.Max(0, vB);       }       pOut[0] = (byte)vB;       pOut[1] = (byte)vG;       pOut[2] = (byte)vR;      }      pIn += 3;      pOut += 3;     }// end of x     pIn += srcData.Stride - w * 3;     pOut += srcData.Stride - w * 3;    } // end of y   }   bmpobj.UnlockBits(srcData);   bmpRtn.UnlockBits(dstData);   bmpobj = bmpRtn;  }  /// <summary>  /// 图片二值化  /// </summary>  /// <param name="hsb"></param>  public void BitmapTo1Bpp(Double hsb)  {   int w = bmpobj.Width;   int h = bmpobj.Height;   Bitmap bmp = new Bitmap(w, h, PixelFormat.Format1bppIndexed);   BitmapData data = bmp.LockBits(new Rectangle(0, 0, w, h), ImageLockMode.ReadWrite, PixelFormat.Format1bppIndexed);   for (int y = 0; y < h; y++)   {    byte[] scan = new byte[(w + 7) / 8];    for (int x = 0; x < w; x++)    {     Color c = bmpobj.GetPixel(x, y);     if (c.GetBrightness() >= hsb) scan[x / 8] |= (byte)(0x80 >> (x % 8));    }    Marshal.Copy(scan, 0, (IntPtr)((int)data.Scan0 + data.Stride * y), scan.Length);   }   bmp.UnlockBits(data);   bmpobj = bmp;  } }}