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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(" ", "");
}
}
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c#识别验证码图片通用类
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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;
}
}
}
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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。