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
}
///
/// 根据RGB，计算灰度值
///
/// Color值
/// 灰度值，整型
private int GetGrayNumColor(System.Drawing.Color posClr)
{
return (posClr.R * 19595 + posClr.G * 38469 + posClr.B * 7472) >> 16;
}
///
/// 灰度转换,逐点方式
///
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));
}
}
}
///
/// 去图形边框
///
///
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));
}
}
}
///
/// 灰度转换,逐行方式
///
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);
}
///
/// 得到有效图形并调整为可平均分割的大小
///
/// 灰度背景分界值
/// 有效字符数
///
/// 得到有效图形,图形为类变量
///
/// 灰度背景分界值
/// 有效字符数
///
/// 得到有效图形,图形由外面传入
///
/// 灰度背景分界值
/// 有效字符数
///
/// 平均分割图片
///
/// 水平上分割数
/// 垂直上分割数
/// 分割好的图片数组
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;
}
///
/// 返回灰度图片的点阵描述字串，1表示灰点，0表示背景
///
/// 灰度图
/// 背前景灰色界限
///
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。