C# · 12月 29, 2021

c#实现识别图片上的验证码数字

public void imgdo(Bitmap img) { //去色 Bitmap btp = img; Color c = new Color(); int rr,gg,bb; for (int i = 0; i < btp.Width; i++) { for (int j = 0; j < btp.Height; j++) { //取图片当前的像素点 c = btp.GetPixel(i,j); rr = c.R; gg = c.G; bb = c.B; //改变颜色 if (rr == 102 && gg == 0 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i,j,Color.FromArgb(255,255,255)); } if (rr == 153 && gg == 0 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i,255)); } if (rr == 153 && gg == 0 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i,255)); } if (rr == 153 && gg == 43 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i,255)); } if (rr == 255 && gg == 255 && bb == 0) { //重新设置当前的像素点 btp.SetPixel(i,255)); } if (rr == 255 && gg == 255 && bb == 51) { //重新设置当前的像素点 btp.SetPixel(i,255)); } } } btp.Save(“d:\\去除相关颜色.png”); picture@R_544_2419@2.Image = Image.FromFile(“d:\\去除相关颜色.png”); //灰度 Bitmap bmphd = btp; for (int i = 0; i < bmphd.Width; i++) { for (int j = 0; j < bmphd.Height; j++) { //取图片当前的像素点 var color = bmphd.GetPixel(i,j); var gray = (int)(color.R * 0.001 + color.G * 0.700 + color.B * 0.250); //重新设置当前的像素点 bmphd.SetPixel(i,Color.FromArgb(gray,gray,gray)); } } bmphd.Save(“d:\\灰度.png”); picture@R_544_2419@27.Image = Image.FromFile(“d:\\灰度.png”); //二值化 Bitmap erzhi = bmphd; Bitmap orcbmp; int nn = 3; int w = erzhi.Width; int h = erzhi.Height; BitmapData data = erzhi.LockBits(new Rectangle(0,w,h),ImageLockMode.ReadOnly,PixelFormat.Format24bppRgb); unsafe { byte* p = (byte*)data.Scan0; byte[,] vSource = new byte[w,h]; int offset = data.Stride – w * nn; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { vSource[x,y] = (byte)(((int)p[0] + (int)p[1] + (int)p[2]) / 3); p += nn; } p += offset; } erzhi.UnlockBits(data); Bitmap bmpDest = new Bitmap(w,h,PixelFormat.Format24bppRgb); BitmapData dataDest = bmpDest.LockBits(new Rectangle(0,ImageLockMode.writeonly,PixelFormat.Format24bppRgb); p = (byte*)dataDest.Scan0; offset = dataDest.Stride – w * nn; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { p[0] = p[1] = p[2] = (int)vSource[x,y] > 161 ? (byte)255 : (byte)0; //p[0] = p[1] = p[2] = (int)GetAverageColor(vSource,x,y,h) > 50 ? (byte)255 : (byte)0; p += nn; } p += offset; } bmpDest.UnlockBits(dataDest); orcbmp = bmpDest; orcbmp.Save(“d:\\二值化.png”); picture@R_544_2419@29.Image = Image.FromFile(“d:\\二值化.png”); } //OCR的值 if (orcbmp != null) { string result = Ocr(orcbmp); label32.Text = result.Replace(“\n”,”\r\n”).Replace(” “,””); } }

C#识别验证码图片通用类

using System;using System.Collections.Generic;using System.Text;using System.Collections;using System.Drawing;using System.Drawing.Imaging;using System.Runtime.InteropServices; namespace BallotAiying2{ class UnCodebase { public Bitmap bmpobj; public UnCodebase(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,255)); } } } /// <summary> /// 灰度转换,逐行方式 /// </summary> public void GrayByLine() { Rectangle rec = new Rectangle(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,len); //对图片进行处理 int GrayValue = 0; for (int i = 0; i < len; i++) { GrayValue = GetGrayNumColor(Color.FromArgb(pixels)); pixels = (byte)(Color.FromArgb(GrayValue,GrayValue,GrayValue)).ToArgb(); //Color转byte } bmpobj.UnlockBits(bmpData); } /// <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,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,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; } }}

以上2则都是使用C#实现的orc识别的代码,希望对大家学习C#有所帮助。