最近写了几个网站的验证码图片自动识别程序,尽管每个网站的验证码图片都不相同,识别的方法有所差别。但写得多了,也总结出不少相同之处。今天抽空封装出一个基础类来,发现可以很好地重复利用,编写不同的验证码识别程序,效率提高了不少。好东东不能独享,现放出来供大家共同研究,请网友们妥善用之。
封装后的类使用很简单,针对不同的验证码,相应继承修改某些方法,即可简单几句代码就可以实现图片识别了:
GrayByPixels(); //灰度处理
GetPicValidByValue(128, 4); //得到有效空间
Bitmap[] pics = GetSplitPics(4, 1); //分割
string code = GetSingleBmpCode(pics[i], 128); //得到代码串
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, 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); } /**//// <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; } } }