C#验证码破解帮助类

http://blog.csdn.net/stevenkylelee/article/details/8263890

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http://outofmemory.cn/code-snippet/2037/c-pojie-yanzhengma-example-code

http://outofmemory.cn/code-snippet/3086/C-yanzheng-code-identify-class

http://www.sufeinet.com/thread-1514-1-1.html

http://lichengguizy.blog.163.com/blog/static/117718586201201111404824/

 

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public class GetImageValue
    {
        //设定图片RGB字符串
        string[] ArrayList = new string[]{
            "00011100011111110110001111000001110000011100000111000001110000011100000111000001011000110111111100011100",  //0
            "00111000111110001111100000011000000110000001100000011000000110000001100000011000000110001111111111111111",  //1
            "01111100111111101000001100000011000000110000011000001100000110000011000001100000110000001111111111111111",  //2
            "01111100111111111000001100000011000001100111100001111110000001110000001100000011100001111111111001111100",  //3
            "00001100000111000001110000111100011011000110110010001100110011001111111110111111000011000000110000001100",  //4
            "11111111111111111100000011000000110000001111100011111110000001110000001100000011100001111111111001111100",  //5
            "00011110001111110110000101100000110000001101111011101111111000111100000101000001011000110110111100011110",  //6
            "01111010001111110000000100000000000000110000011000000100000011000000100000011000000110000011000000110000",  //7
            "00111110011111110110001101100011011100100011111000111110011001111100000111000001111000110111111100111110",  //8
            "00011100011110110110001111000001110000011010001101111111001111010000000100000001010000110101110000111100",  //9
            "00111000111111101000010010000011100000111000001110000011000000111000001110000011110001001111011000111000",  //10
            "00001100011111000111110000001100000011000000110000001100000011000000110000001100000011000111110101111111",  //11
            "11111000110111000000010000000110000001100000110000011000001100000110000011000000100000000101111011111110",  //12
            "10111000111111100000001000000110000011001111000011110100000011100000011000000110000011101111110011111000",  //13
            "00000110000011100000111000001110000101100011011000100110011001001111111111111111000001000000011000000110",  //14
            "11111110111111101000000010000000100000001111000011110100000011100000011000000110000011101111110011111000",  //15
            "00111100011111101100001011000000100000001011110011111110110001111000001110000011110001101111111000111100",  //16
            "11101111111111110000001100000010000001100000010000001000000110000001000000110000001100000110000001100000",  //17
            "01111100111111101100011011000110110001000111110001111100110011101000001110000011110001101101111001111100",  //18
            "01111000111111101100011010000011100000111100011111111111011110110000001100000100100001101111110001111000",  //19
            "00111100011111111100001110000001110000011110001101111111001101010000000000000011010000010111111000111100",  //20=9
            "00111000111111001100011010000011100000011000001100000011100000111000001010000011110001101111010000101000",  //21=0
            "00111000010111010110001111000001110000011110001101111111001111010000000100000011010000100111011000111100",  //22=9
            "00000110000010100000111000010110001101100011011001000110011001101011101111111111000001100000011000000110",  //23=4
            "00011110001011110110000101000000110000001101101011111101011000111100000110000001010000110101111000011110",  //24=6
            "00111100011111101110001101000001110000011110001101111111001111010000000100000011000000110101101000111100",  //25=9
            "11111000111100000000011000000100000000100000110000011000001100000110000001000000100000001111110011111110"   //26=2
        };

        /// <summary>
        /// 获取图片验证码数字
        /// </summary>
        /// <returns></returns>
        public string GetImageValues()
        {
            string url = "http://xxxx.xxxx/image";
            WebRequest myWebRequest = WebRequest.Create(url);
            WebResponse myWebResponse = myWebRequest.GetResponse();
            Stream ReceiveStream = myWebResponse.GetResponseStream();
            Bitmap map = new Bitmap(ReceiveStream, false);
            UnCodebase ucode = new UnCodebase(map);

            ucode.GrayByPixels(); //灰度处理

            Bitmap[] pics = ucode.readMap();
            int[] gray = new int[4];
            for (int j = 0; j < 4; j++)
            {
                gray[j] = ucode.GetSingleDgGrayValue(pics[j]);
            }
            string[] arr = new string[4];
            for (int i = 0; i < 4; i++)
            {
                arr[i] = ucode.GetSingleBmpCode(pics[i], gray[i]);
            }
            string picnum = getPicnums(arr);
            return picnum;
        }

        public string getPicnums(string[] arr)
        {
            string Code = "";
            for (int i = 0; i < 4; i++)
            {
                string code = arr[i];   //得到代码串

                for (int arrayIndex = 0; arrayIndex < ArrayList.Length; arrayIndex++)
                {
                    //逐点判断特征码是否相同，允许误差!
                    char temp1, temp2;
                    int point = 0;
                    if (ArrayList[arrayIndex].Equals(code))
                    {
                        point = 0;
                        if (arrayIndex > 9)
                        {
                            if (arrayIndex == 20 || arrayIndex == 22 || arrayIndex == 25)
                            {
                                Code = Code + "9";
                            }
                            else if (arrayIndex == 21)
                            {
                                Code = Code + "0";
                            }
                            else if (arrayIndex == 23)
                            {
                                Code = Code + "4";
                            }
                            else if (arrayIndex == 24)
                            {
                                Code = Code + "6";
                            }
                            else if (arrayIndex == 26)
                            {
                                Code = Code + "2";
                            }
                            else
                            {
                                Code = Code + (arrayIndex - 10).ToString();
                            }
                        }
                        else
                        {
                            Code = Code + arrayIndex.ToString();
                        }
                        break;
                    }
                    else
                    {
                        //将字符串数组，直接转为单个字符进行对比，并记录不相同的点
                        for (int Comparison = 0; Comparison < code.Length; Comparison++)
                        {
                            temp1 = arr[i][Comparison];
                            temp2 = ArrayList[arrayIndex][Comparison];
                            if (temp1 != temp2)
                            {
                                point = point + 1;
                            }
                        }
                    }

                    //当不相同点的值小于10的时候，也就是说误差点小于10的时候则直接等于此数字，否则将跳出循环继续对下一个特征码进行判断
                    if (point < 10)
                    {
                        if (arrayIndex > 9)
                        {
                            if (arrayIndex == 20 || arrayIndex == 22 || arrayIndex == 25)
                            {
                                Code = Code + "9";
                            }
                            else if (arrayIndex == 21)
                            {
                                Code = Code + "0";
                            }
                            else if (arrayIndex == 23)
                            {
                                Code = Code + "4";
                            }
                            else if (arrayIndex == 24)
                            {
                                Code = Code + "6";
                            }
                            else if (arrayIndex == 26)
                            {
                                Code = Code + "2";
                            }
                            else
                            {
                                Code = Code + (arrayIndex - 10).ToString();
                            }
                        }
                        else
                        {
                            Code = Code + arrayIndex.ToString();
                        }
                        break;
                    }
                }
            }
            return Code;
        }


-------------------------图片处理类

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;
        }

        public Bitmap[] readMap()
        {
            string str;
            RectangleF[] block = new RectangleF[4];
            block[0] = new Rectangle(7, 3, 8, 13);
            block[1] = new Rectangle(20, 3, 8, 13);
            block[2] = new Rectangle(33, 3, 8, 13);
            block[3] = new Rectangle(47, 3, 8, 13);
            //分别克隆图片的四个部分    
            Bitmap[] s = new Bitmap[4];
            s[0] = bmpobj.Clone(block[0], PixelFormat.DontCare);
            s[1] = bmpobj.Clone(block[1], PixelFormat.DontCare);
            s[2] = bmpobj.Clone(block[2], PixelFormat.DontCare);
            s[3] = bmpobj.Clone(block[3], PixelFormat.DontCare);
            return s;
        }

        /**/
        /// <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>
        /// 得到单个灰度图像前景背景的临界值 最大类间方差法，yuanbao,2007.08
        /// </summary>
        /// <returns>前景背景的临界值</returns>
        public int GetSingleDgGrayValue(Bitmap singlepic)
        {
            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
            int step = 1;
            //生成直方图
            for (int i = 0; i < singlepic.Width; i++)
            {
                for (int j = 0; j < singlepic.Height; j++)
                {
                    //返回各个点的颜色，以RGB表示
                    pixelNum[singlepic.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>
        /// 得到灰度图像前景背景的临界值 最大类间方差法，yuanbao,2007.08
        /// </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
            int step = 1;
            //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;
        }

    }