一種細(xì)化算法及其與opencv的實現(xiàn)

1、一種細(xì)化算法及其與 opencv 的實現(xiàn) 是根據(jù)圖像中像素點得八個相鄰點得情況，得到一個索 引值，然后查表，如果為 0 怎保留該點，否則刪除 算法代碼： cpp view plaincopy #include stdafx.h #include cv.h #include highgui.h #include cxcore.h #includeiostream #includefstream #includeiomanip using namespace std; static int erasetable256 = 0,0,1,1,0,0,1,1, 1,1,0,1,1,1,0,1, 0,0,

2、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, 0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0

3、, 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 0 則保留， fan ;/ 這個表是檢測是用來細(xì)化黑色點邊緣的，若為 否則刪除，如果用來細(xì)化白色點邊緣的話就取 /* * *888 函數(shù)名： save 參數(shù)類型： void 功能：保存細(xì)化查詢表 * * void save() fstream writefi

4、le(erasetable.txt , ios:out); int n=0; for(int i=0;i256;i+) writefilesetw(2)erasetablei; writefileendl; /* *88 函數(shù)名： npow 參數(shù)類型： int n 功能：求 2 的 n 次方并返回結(jié)果 返回值類型： int * */ int npow(int n) int mul = 1; for(int i=0;in;i+) mul *= 2; return mul; /* * 函數(shù)名： Threshold 參數(shù)類型： IplImage *src , int lower , int high

5、er 功能：二值化灰度圖像 * */ void Threshold(IplImage *src , int lower , int higher) assert(src-nChannels=1); for(int h=0;hsrc-height;h+) for(int w=0;wsrc-width;w+) if(*(src-imageData +h*src-widthStep+w)0*(src-imageD ata+h*src-widthStep+w)87) *(src-imageData +h*src-widthStep+w) = 255; else *(src-imageData +h*s

6、rc-widthStep+w) = 0; /* *8 函數(shù)名： scantable 參數(shù)類型： IplImage *src 功能：掃描像素 8 領(lǐng)域周圍的八個像素值(只檢測白色點得 周圍)，像素值為 0置 1，否則為 0，并保存(如果是檢測黑 色的周圍的話就相反) ， 再根據(jù)得到的數(shù)，將得到的數(shù)看做一個二進(jìn)制數(shù)化為十進(jìn)制 的數(shù)，這個值即為查詢索引，如果查到的值為 0 則保留，否 則刪除 * */ void scantable(IplImage *src) assert(src-nChannels=1); int scan8 = 0; for(int h=1;h(src-height-1);h+

7、) for(int w=1;w(src-width-1);w+) int index = 0; if(*(src-imageData+(h)*src-widthStep+w)!=0) if(*(src-imageData+(h-1)*src-widthStep+w-1)=0) scan0 = 1; else scan0 = 0; if(*(src-imageData+(h-1)*src-widthStep+w)=0) scan1 = 1; else scan1 = 0; if(*(src-imageData+(h-1)*src-widthStep+w+1)=0) scan2 = 1; else

8、 scan2 = 0; if(*(src-imageData+(h)*src-widthStep+w-1)=0) scan3 = 1; else scan3 = 0; if(*(src-imageData+(h)*src-widthStep+w+1)=0) scan4 = 1; else scan4 = 0; if(*(src-imageData+(h+1)*src-widthStep+w-1)=0) scan5 = 1; else scan5 = 0; if(*(src-imageData+(h+1)*src-widthStep+w)=0) scan6 = 1; else scan6 = 0

9、; if(*(src-imageData+(h+1)*src-widthStep+w+1)=0) scan7 = 1; else scan7 = 0; for(int i=0;i8;i+) index += scani*npow(i); / printf(%dn ,index); if(erasetableindex = 1) /printf(%dn , erasetableindex); *(src-imageData+h*src-widthStep+w) = 0; int _tmain(int argc, _TCHAR* argv) save(); IplImage *img = 0; I

10、plImage *gray = 0; IplImage *copy_gray = 0; int vmin = 0; int vmax = 0; img = cvLoadImage(1.bmp , 1); gray = cvCreateImage(cvGetSize(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_g