一种细化算法及其与opencv的实现

1、一种细化算法及其与opencv的实现是根据图像中像素点得八个相邻点得情况，得到一个索引值，然后查表，如果为0怎保留该点，否则删除算法代码：cppviewplaincopy#includestdafx.h#includecv.h#includehighgui.h#includecxcore.h#include<iostream>#include<fstream>#include<iomanip>usingnamespacestd;staticinterasetable256=0,0,1,1,0,0,1,1,1,1

2、,0,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,0,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,0,1,1,0,1,1,1,0,1,0,0,0,0,0,0,0,1

3、,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,0,1,0,0,0,0,0,0,0,0,1,1,0,1,1,1,0,1,0,0,0,0,0,0,0,1,1,1,0,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,0,0,1,1,0,0,1,0,0,0; 这个表是检测是用来细化黑色点边缘的， 若为否则删除，如果用来细化白色点边缘的话就取1a*函数名：save参数类型：void功能：保存细化查询表*8880则保留,fan*voidsave()fstreamwrite

4、file(erasetable.txt,ios:out);intn=0;for(inti=0;i<256;i+)writefile<<setw(2)<<erasetablei;writefile<<endl;尸*88npow参数类型：intn功能：求2的n次方并返回结果返回值类型：int*/intnpow(intn)intmul=1;for(inti=0;i<n;i+)(mul*=2;)returnmul;)1a*函数名：Threshold参数类型：IplImage*src,intl

5、ower,inthigher功能：二值化灰度图像*;voidThreshold(IplImage*src,intlower,inthigher)(assert(src->nChannels=1);for(inth=0;h<src->height;h+)for(intw=0;w<src->width;w+)(if(*(src->imageData+h*src->widthStep+w)>0&&*(src->imageData+h*src-&

6、amp;gt;widthStep+w)<87)*(src->imageData+h*src->widthStep+w)=255;else*(src->imageData+h*src->widthStep+w)=0;1a*8函数名：scantable参数类型：IplImage*src功能：扫描像素8领域周围的八个像素值(只检测白色点得周围)，像素值为。置1,否则为0,并保存(如果是检测黑色的周围的话就相反)，再根据得到的数，将得到的数看做一个二进制数化为十进制的数，这个值即为查询索引，如果查到的值为0则保留，否则删除*/voi

7、dscantable(IplImage*src)assert(src->nChannels=1);intscan8=0;for(inth=1;h<(src->height-1);h+)for(intw=1;w<(src->width-1);w+)intindex=0;if(*(src->imageData+(h)*src->widthStep+w)!=0)if(*(src->imageData+(h-1)*src->widthStep+w-1)=0)scan0=1;el

8、sescan0=0;if(*(src->imageData+(h-1)*src->widthStep+w)=0)scan1=1;elsescan1=0;if(*(src->imageData+(h-1)*src->widthStep+w+1)=0)scan2=1;elsescan2=0;if(*(src->imageData+(h)*src->widthStep+w-1)=0)scan3=1;elsescan3=0;if(*(src->imageData+(h)*src->width

9、Step+w+1)=0)scan4=1;elsescan4=0;if(*(src->imageData+(h+1)*src->widthStep+w-1)=0)scan5=1;elsescan5=0;if(*(src->imageData+(h+1)*src->widthStep+w)=0)scan6=1;elsescan6=0;if(*(src->imageData+(h+1)*src->widthStep+w+1)=0)scan7=1;elsescan7=0;for(inti=0;i<8;i+

10、)index+=scani*npow(i);/printf(%dn,index);if(erasetableindex=1)printf(%dn,erasetableindex);*(src->imageData+h*src->widthStep+w)=0;int_tmain(intargc,_TCHAR*argv)(save();IplImage*img=0;IplImage*gray=0;IplImage*copy_gray=0;intvmin=0;intvmax=0;img=cvLoadImage(1.bmp,1);gray=cvCreateImage(cvG

11、etSize(img),8,1);copy_gray=cvCreateImage(cvGetSize(img),8,1);cvCvtColor(img,gray,CV_BGR2GRAY);cvSmooth(gray,gray,CV_MEDIAN,3,0,0,0);cvNamedWindow(gray”,1);cvNamedWindow(erase,1);cvCreateTrackbar(lower,gray,&vmin,256,0);/cvCreateTrackbar(higher,gray,&vmax,256,0);Threshold(gray,vmin,vmax);cvCopy(gray,copy_gray);scantable(copy