C#验证码识别类
C#验证码识别类，可以用于识别各种验证码的算法演示
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; } } }