opencv實現二值影象的細化
阿新 • • 發佈:2019-02-11
opencv實現二值影象細化的演算法
細化演算法通常和骨骼化、骨架化演算法是相同的意思,也就是thin演算法或者skeleton演算法。雖然很多影象處理的教材上不是這麼寫的,具體原因可以看這篇論文,Louisa Lam, Seong-Whan Lee, Ching Y. Suen,“Thinning Methodologies-A Comprehensive Survey ”,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 14, NO. 9, SEPTEMBER 1992 ,總結了幾乎所有92年以前的經典細化演算法。
函式:void cvThin( IplImage* src, IplImage* dst, int iterations=1)
功能:將IPL_DEPTH_8U型二值影象進行細化
引數:src,原始IPL_DEPTH_8U型二值影象
dst,目標儲存空間,必須事先分配好,且和原影象大小型別一致
iterations,迭代次數
參考文獻:T. Y. Zhang and C. Y. Suen, “A fast parallel algorithm for thinning digital patterns,” Comm. ACM, vol. 27, no. 3, pp. 236-239, 1984.
void cvThin( IplImage* src, IplImage* dst, int iterations=1) { CvSize size = cvGetSize(src); cvCopy(src, dst); int n = 0,i = 0,j = 0; for(n=0; n<iterations; n++) { IplImage* t_image = cvCloneImage(dst); for(i=0; i<size.height; i++) { for(j=0; j<size.width; j++) { if(CV_IMAGE_ELEM(t_image,byte,i,j)==1) { int ap=0; int p2 = (i==0)?0:CV_IMAGE_ELEM(t_image,byte, i-1, j); int p3 = (i==0 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte, i-1, j+1); if (p2==0 && p3==1) { ap++; } int p4 = (j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte,i,j+1); if(p3==0 && p4==1) { ap++; } int p5 = (i==size.height-1 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j+1); if(p4==0 && p5==1) { ap++; } int p6 = (i==size.height-1)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j); if(p5==0 && p6==1) { ap++; } int p7 = (i==size.height-1 || j==0)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j-1); if(p6==0 && p7==1) { ap++; } int p8 = (j==0)?0:CV_IMAGE_ELEM(t_image,byte,i,j-1); if(p7==0 && p8==1) { ap++; } int p9 = (i==0 || j==0)?0:CV_IMAGE_ELEM(t_image,byte,i-1,j-1); if(p8==0 && p9==1) { ap++; } if(p9==0 && p2==1) { ap++; } if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7) { if(ap==1) { if(!(p2 && p4 && p6)) { if(!(p4 && p6 && p8)) { CV_IMAGE_ELEM(dst,byte,i,j)=0; } } } } } } } cvReleaseImage(&t_image); t_image = cvCloneImage(dst); for(i=0; i<size.height; i++) { for(int j=0; j<size.width; j++) { if(CV_IMAGE_ELEM(t_image,byte,i,j)==1) { int ap=0; int p2 = (i==0)?0:CV_IMAGE_ELEM(t_image,byte, i-1, j); int p3 = (i==0 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte, i-1, j+1); if (p2==0 && p3==1) { ap++; } int p4 = (j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte,i,j+1); if(p3==0 && p4==1) { ap++; } int p5 = (i==size.height-1 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j+1); if(p4==0 && p5==1) { ap++; } int p6 = (i==size.height-1)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j); if(p5==0 && p6==1) { ap++; } int p7 = (i==size.height-1 || j==0)?0:CV_IMAGE_ELEM(t_image,byte,i+1,j-1); if(p6==0 && p7==1) { ap++; } int p8 = (j==0)?0:CV_IMAGE_ELEM(t_image,byte,i,j-1); if(p7==0 && p8==1) { ap++; } int p9 = (i==0 || j==0)?0:CV_IMAGE_ELEM(t_image,byte,i-1,j-1); if(p8==0 && p9==1) { ap++; } if(p9==0 && p2==1) { ap++; } if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7) { if(ap==1) { if(p2*p4*p8==0) { if(p2*p6*p8==0) { CV_IMAGE_ELEM(dst, byte,i,j)=0; } } } } } } } cvReleaseImage(&t_image); } }
例項
//使用舉例
#include "cxcore.h"
#include "cv.h"
#include "highgui.h"
int main(int argc, char* argv[])
{
if(argc!=2)
{
return 0;
}
IplImage *pSrc = NULL,*pDst = NULL,*pTmp = NULL;
//傳入一個灰度影象
pSrc = cvLoadImage(argv[1],CV_LOAD_IMAGE_GRAYSCALE);
if(!pSrc)
{
return 0;
}
pTmp = cvCloneImage(pSrc);
pDst = cvCreateImage(cvGetSize(pSrc),pSrc->depth,pSrc->nChannels);
cvZero(pDst);
cvThreshold(pSrc,pTmp,128,1,CV_THRESH_BINARY_INV);//做二值處理,將影象轉換成0,1格式
//cvSaveImage("c://Threshold.bmp",pTmp,0);
cvThin(pTmp,pDst,8);//細化,通過修改iterations引數進一步細化
cvNamedWindow("src",1);
cvNamedWindow("dst",1);
cvShowImage("src",pSrc);
//將二值影象轉換成灰度,以便顯示
int i = 0,j = 0;
CvSize size = cvGetSize(pDst);
for(i=0; i<size.height; i++)
{
for(j=0; j<size.width; j++)
{
if(CV_IMAGE_ELEM(pDst,uchar,i,j)==1)
{
CV_IMAGE_ELEM(pDst,uchar,i,j) = 0;
}
else
{
CV_IMAGE_ELEM(pDst,uchar,i,j) = 255;
}
}
}
//cvSaveImage("c://thin.bmp",pDst);
cvShowImage("dst",pDst);
cvWaitKey(0);
cvReleaseImage(&pSrc);
cvReleaseImage(&pDst);
cvReleaseImage(&pTmp);
cvDestroyWindow("src");
cvDestroyWindow("dst");
return 0;
}