关于验证码识别2

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 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
          

            具体使用，请参见我做的例子：
                 投票程序示例.exe      投票程序源码
       （例子说明：使用进程投票，可自动清除Alert弹出窗口，可自动换IP，ADSL用户自行修改Restart.bat中第三行内容）

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;
        }
    }
}

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关于验证码识别2

标签：blog   http   color   使用   os   io   for   ar   

原文地址：http://www.cnblogs.com/Bonker/p/3912590.html