C#验证码识别类完整实例

本文实例讲述了C#验证码识别类。分享给大家供大家参考。具体实现方法如下：

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;
  }
 }
}

希望本文所述对大家的C#程序设计有所帮助。