c#实现识别图片上的验证码数字
投稿:hebedich
这篇文章主要介绍了c#实现识别图片上的验证码数字的方法,本文给大家汇总了2种方法,有需要的小伙伴可以参考下。

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, 255));
}
if (rr == 153 && gg == 0 && bb == 0)
{
//重新设置当前的像素点
btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255));
} if (rr == 153 && gg == 0 && bb == 51)
{
//重新设置当前的像素点
btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255));
} if (rr == 153 && gg == 43 && bb == 51)
{
//重新设置当前的像素点
btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255));
}
if (rr == 255 && gg == 255 && bb == 0)
{
//重新设置当前的像素点
btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255));
}
if (rr == 255 && gg == 255 && bb == 51)
{
//重新设置当前的像素点
btp.SetPixel(i, j, Color.FromArgb(255, 255, 255, 255));
}
}
}
btp.Save("d:\\去除相关颜色.png");
pictureBox2.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, j, Color.FromArgb(gray, gray, gray));
}
}
bmphd.Save("d:\\灰度.png");
pictureBox27.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, 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, 0, w, h), 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, w, h) > 50 ? (byte)255 : (byte)0;
p += nn;
}
p += offset;
}
bmpDest.UnlockBits(dataDest);
orcbmp = bmpDest;
orcbmp.Save("d:\\二值化.png");
pictureBox29.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, 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));
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, 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;
}
}
}
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。
