在车牌识别系统中， 车牌字符可以正确切割的前提是车牌图像可以水平，以至于水平投影和垂直投影可以正常进行。假设车牌倾斜没有矫正。那么水平投影和垂直投影，甚至铆钉都无法正常处理。所以。当车辆信息中获取车牌的第一步，应该是检查倾斜角度，做倾斜矫正。
倾斜矫正，这里使用的算法：
1、倾斜角度检測： 霍夫变换
关于hough变换，能够參考前面图像处理博文：
http://blog.csdn.net/liujia2100/article/details/6989693 直线检測
http://blog.csdn.net/liujia2100/article/details/6989688 文本图像倾斜矫正
2、倾斜矫正： 图像旋转
以下具体说明倾斜矫正过程：
原车牌图像为（从车牌图像中，能够看到车牌有倾斜角度）：
1、 获取车牌在车辆中的粗略位置（能够用多种方法，这里暂不分析）
2、提取车牌总体图片数据。 依据第一步结果。提取出。车牌在辆大体位置信息。
关于车牌定位，我使用两部。第一步粗略定位，然后做一些预处理。比方倾斜矫正，然后第二部才是精确定位，仅仅提取车牌的位置信息图像
3、利用HSV颜色空间转换，获取车牌背景蓝色区域位置，获取车牌粗略信息图像后，因为车牌背景颜色与周围颜色有非常明显的差别。这里採用HSV颜色过滤的方法，过滤绿色背景图像
4、水平膨胀。 水平膨胀的目的。是为了边缘检測，仅仅要求检測边缘，尽量除去字符信息，也能够减少hough变换的运算量
5、水平差分运算，相当于 边缘检測。经过上面的处理后。才进行边缘检測
6、这个时候就能够利用hough变换检測直线了。
因为hough变换运算量十分大。所以。尽量降低图像中的白点，来降低计算量，因此前面才做了这么多步骤。
请看下图的红线，就是检測出来的角度。为177度（Hough代码在以下）。
7、利用旋转算法，旋转刚才粗略提取的车牌位置（旋转代码在以下），虽然旋转后的车牌有些锯齿。可是已经可以保证水平，就行使用水平投影和垂直投影了
这是旋转后的车牌，有些锯齿出现。因为图像分辨率较低。就没实用差值运算。
8、精确提取车牌
9、正常切割字符
10、识别结果
因为正弦余弦运算，计算量比較大，这里进行一部分优化。就是正弦余弦计算用数组取代。
生成正弦。余弦数组的的代码例如以下：
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
int main(void)
{
char buf[20];
int i;
float p;
float k;
FILE *fcos;
FILE *fsin;
fcos = fopen(".\cos.txt", "wb");
fsin = fopen(".\sin.txt", "wb");
if(fcos == NULL || fsin == NULL)
{
printf("open error
");
exit(-1);
}
i = 0;
for(i = 0; i <= 180; i++)
{
k = 3.1415926 * i / 180.0;
p = cos(k);
if((i%16 == 0))
fwrite("
",strlen("
"),1,fcos);
sprintf(buf,"%f, ", p);
fwrite(buf,strlen(buf),1,fcos);
}
for(i = 0; i <= 180; i++)
{
k = 3.1415926 * i / 180.0;
p = sin(k);
if((i%16 == 0))
fwrite("
",strlen("
"),1,fsin);
sprintf(buf,"%f, ", p);
fwrite(buf,strlen(buf),1,fsin);
}
fclose(fcos);
fclose(fsin);
return 0;
}生成数组为：
float carCos[] = {
1.000000, 0.999848, 0.999391, 0.998630, 0.997564, 0.996195, 0.994522, 0.992546, 0.990268, 0.987688, 0.984808, 0.981627, 0.978148, 0.974370, 0.970296, 0.965926,
0.961262, 0.956305, 0.951057, 0.945519, 0.939693, 0.933580, 0.927184, 0.920505, 0.913545, 0.906308, 0.898794, 0.891007, 0.882948, 0.874620, 0.866025, 0.857167,
0.848048, 0.838671, 0.829038, 0.819152, 0.809017, 0.798636, 0.788011, 0.777146, 0.766044, 0.754710, 0.743145, 0.731354, 0.719340, 0.707107, 0.694658, 0.681998,
0.669131, 0.656059, 0.642788, 0.629320, 0.615662, 0.601815, 0.587785, 0.573576, 0.559193, 0.544639, 0.529919, 0.515038, 0.500000, 0.484810, 0.469472, 0.453991,
0.438371, 0.422618, 0.406737, 0.390731, 0.374607, 0.358368, 0.342020, 0.325568, 0.309017, 0.292372, 0.275637, 0.258819, 0.241922, 0.224951, 0.207912, 0.190809,
0.173648, 0.156434, 0.139173, 0.121869, 0.104528, 0.087156, 0.069757, 0.052336, 0.034900, 0.017452, 0.000000, -0.017452, -0.034899, -0.052336, -0.069756, -0.087156,
-0.104528, -0.121869, -0.139173, -0.156434, -0.173648, -0.190809, -0.207912, -0.224951, -0.241922, -0.258819, -0.275637, -0.292372, -0.309017, -0.325568, -0.342020, -0.358368,
-0.374607, -0.390731, -0.406737, -0.422618, -0.438371, -0.453990, -0.469472, -0.484810, -0.500000, -0.515038, -0.529919, -0.544639, -0.559193, -0.573576, -0.587785, -0.601815,
-0.615661, -0.629320, -0.642788, -0.656059, -0.669131, -0.681998, -0.694658, -0.707107, -0.719340, -0.731354, -0.743145, -0.754710, -0.766044, -0.777146, -0.788011, -0.798635,
-0.809017, -0.819152, -0.829038, -0.838671, -0.848048, -0.857167, -0.866025, -0.874620, -0.882948, -0.891007, -0.898794, -0.906308, -0.913545, -0.920505, -0.927184, -0.933580,
-0.939693, -0.945519, -0.951056, -0.956305, -0.961262, -0.965926, -0.970296, -0.974370, -0.978148, -0.981627, -0.984808, -0.987688, -0.990268, -0.992546, -0.994522, -0.996195,
-0.997564, -0.998630, -0.999391, -0.999848, -1.000000
};
float carSin[] = {
0.000000, 0.017452, 0.034899, 0.052336, 0.069756, 0.087156, 0.104528, 0.121869, 0.139173, 0.156434, 0.173648, 0.190809, 0.207912, 0.224951, 0.241922, 0.258819,
0.275637, 0.292372, 0.309017, 0.325568, 0.342020, 0.358368, 0.374607, 0.390731, 0.406737, 0.422618, 0.438371, 0.453990, 0.469472, 0.484810, 0.500000, 0.515038,
0.529919, 0.544639, 0.559193, 0.573576, 0.587785, 0.601815, 0.615661, 0.629320, 0.642788, 0.656059, 0.669131, 0.681998, 0.694658, 0.707107, 0.719340, 0.731354,
0.743145, 0.754710, 0.766044, 0.777146, 0.788011, 0.798635, 0.809017, 0.819152, 0.829038, 0.838671, 0.848048, 0.857167, 0.866025, 0.874620, 0.882948, 0.891007,
0.898794, 0.906308, 0.913545, 0.920505, 0.927184, 0.933580, 0.939693, 0.945519, 0.951056, 0.956305, 0.961262, 0.965926, 0.970296, 0.974370, 0.978148, 0.981627,
0.984808, 0.987688, 0.990268, 0.992546, 0.994522, 0.996195, 0.997564, 0.998630, 0.999391, 0.999848, 1.000000, 0.999848, 0.999391, 0.998630, 0.997564, 0.996195,
0.994522, 0.992546, 0.990268, 0.987688, 0.984808, 0.981627, 0.978148, 0.974370, 0.970296, 0.965926, 0.961262, 0.956305, 0.951057, 0.945519, 0.939693, 0.933580,
0.927184, 0.920505, 0.913545, 0.906308, 0.898794, 0.891007, 0.882948, 0.874620, 0.866025, 0.857167, 0.848048, 0.838671, 0.829038, 0.819152, 0.809017, 0.798636,
0.788011, 0.777146, 0.766044, 0.754710, 0.743145, 0.731354, 0.719340, 0.707107, 0.694658, 0.681998, 0.669131, 0.656059, 0.642788, 0.629320, 0.615662, 0.601815,
0.587785, 0.573576, 0.559193, 0.544639, 0.529919, 0.515038, 0.500000, 0.484810, 0.469472, 0.453991, 0.438371, 0.422618, 0.406737, 0.390731, 0.374607, 0.358368,
0.342020, 0.325568, 0.309017, 0.292372, 0.275637, 0.258819, 0.241922, 0.224951, 0.207912, 0.190809, 0.173648, 0.156435, 0.139173, 0.121869, 0.104529, 0.087156,
0.069757, 0.052336, 0.034900, 0.017452, 0.000000
};
旋转RGB图像的主要函数：
image： 图像数据
iRotateAngle: 要旋转的角度
width， height：原始图像的宽度。高度
lwidth。lheight：旋转后图像的宽度，高度
unsigned char *RotateRGB(unsigned char *image, float iRotateAngle,int width,int height,int &lwidth,int &lheight)
{
int i,j,k,m,n;
long lNewWidth;
long lNewHeight;
float gray;
long i0;
long j0;
float fRotateAngle;
float fSina, fCosa;
float fSrcX1,fSrcY1,fSrcX2,fSrcY2,fSrcX3,fSrcY3,fSrcX4,fSrcY4;
float fDstX1,fDstY1,fDstX2,fDstY2,fDstX3,fDstY3,fDstX4,fDstY4;
float f1,f2;
if(iRotateAngle >= 0)
{
fSina = (float)carSin[(int)iRotateAngle];
fCosa = (float)carCos[(int)iRotateAngle];
}
else
{
fSina = 0 - (float)carSin[0 -(int)iRotateAngle];
fCosa = (float)carCos[0 - (int)iRotateAngle];
}
fSrcX1 = (float) (- (width - 1) / 2);
fSrcY1 = (float) ( (height - 1) / 2);
fSrcX2 = (float) ( (width - 1) / 2);
fSrcY2 = (float) ( (height - 1) / 2);
fSrcX3 = (float) (- (width - 1) / 2);
fSrcY3 = (float) (- (height - 1) / 2);
fSrcX4 = (float) ( (width - 1) / 2);
fSrcY4 = (float) (- (height - 1) / 2);
fDstX1 = fCosa * fSrcX1 + fSina * fSrcY1;
fDstY1 = -fSina * fSrcX1 + fCosa * fSrcY1;
fDstX2 = fCosa * fSrcX2 + fSina * fSrcY2;
fDstY2 = -fSina * fSrcX2 + fCosa * fSrcY2;
fDstX3 = fCosa * fSrcX3 + fSina * fSrcY3;
fDstY3 = -fSina * fSrcX3 + fCosa * fSrcY3;
fDstX4 = fCosa * fSrcX4 + fSina * fSrcY4;
fDstY4 = -fSina * fSrcX4 + fCosa * fSrcY4;
lNewWidth = (long) ( max( fabs(fDstX4 - fDstX1), fabs(fDstX3 - fDstX2) ) + 0.5);
lNewHeight = (long) ( max( fabs(fDstY4 - fDstY1), fabs(fDstY3 - fDstY2) ) + 0.5);
unsigned char *temp=myMalloc(lNewHeight*lNewWidth*3,0,0);
f1 = (float) (-0.5 * (lNewWidth - 1) * fCosa - 0.5 * (lNewHeight - 1) * fSina
+ 0.5 * (width - 1));
f2 = (float) ( 0.5 * (lNewWidth - 1) * fSina - 0.5 * (lNewHeight - 1) * fCosa
+ 0.5 * (height - 1));
for(i = 0; i < lNewHeight; i++)
{
for(m=0,j = 0;j < lNewWidth,m<lNewWidth*3;m+=3,j++)
{
i0 = (long) (-((float) j) * fSina + ((float) i) * fCosa + f2 + 0.5);
j0 = (long) ( ((float) j) * fCosa + ((float) i) * fSina + f1 + 0.5);
if( (j0 >= 0) && (j0 < width) && (i0 >= 0) && (i0 < height))
{
n=i0 * width * 3 + j0 * 3;
*(temp + lNewWidth * i * 3 + m + 1) = *(image + n + 1);
*(temp + lNewWidth * i * 3 + m + 2) = *(image + n + 2);
*(temp + lNewWidth * i * 3 + m) = *(image + n);
}
else
{
*(temp + lNewWidth * i*3+ m+1)=0;
*(temp + lNewWidth * i*3+ m+2)=0;
*(temp + lNewWidth * i*3+ m)=0;
}
}
}
lwidth = lNewWidth;
lheight = lNewHeight;
return temp;
}Hough变化的主要函数
返回值Kmax，就是检測到最长直线的角度，就是车牌的倾斜角度。
int hough(unsigned char *srcBmp,int width,int height)
{
int kmax=0;
int pmax=0;
int yuzhi=0;
int i,j,k,m,n,p;
int mp = (int) (sqrt(width*width + height*height)+1);
int ma = 180;//180
int ap;
int npp[180][1000];
for(i=0;i<180;i++)
for(j=0;j<1000;j++)
npp[i][j]=0;
for(i = 0;i < height;i++)
for(j = 0; j < width;j++)
{
if(srcBmp[i * width + j]==255)
{
for(k = 0; k < ma; k++)
{
p=(int)(i * carCos[k] + j * carSin[k]);
p=(int)(p/2 + mp/2);
npp[k][p]=npp[k][p]++;
}
}
}
kmax=0;
pmax=0;
n=0;
for(i = 0; i < ma; i++)
for(j = 0; j < mp; j++)
{
if(npp[i][j] > yuzhi)
{
yuzhi=npp[i][j];
kmax=i;
pmax=j;
}
}
for(i = 0; i < height;i++)
for(j = 0; j < width;j++)
{
if(srcBmp[i*width+j]==255)
{
p=(int)(i*carCos[kmax] + j *carSin[kmax]);
p=(int)(p/2+mp/2);
#if defined(DISPLAYDEBUG)
if(p==pmax)
putpixel(j,i,RGB(255,0,0));
#endif
}
}
return kmax;
}图像处理交流QQ群：
105060236