转自：http://blog.csdn.net/byxdaz/archive/2010/06/02/5642669.aspx
细化算法通常和骨骼化、骨架化算法是相同的意思，也就是thin算法或者skeleton算法。虽然很多图像处理的教材上不是这么写的，具体原因可以看这篇论文，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 ，总结了几乎所有92年以前的经典细化算法。
函数：void cvThin( IplImage* src, IplImage* dst, int iterations=1)功能：将IPL_DEPTH_8U型二值图像进行细化参数：src，原始IPL_DEPTH_8U型二值图像dst，目标存储空间，必须事先分配好，且和原图像大小类型一致iterations，迭代次数参考文献：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); }
}
//使用举例
#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;
//传入一个灰度图像 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);//做二值处理，将图像转换成0，1格式 //cvSaveImage("c://Threshold.bmp",pTmp,0); cvThin(pTmp,pDst,8);//细化，通过修改iterations参数进一步细化 cvNamedWindow("src",1); cvNamedWindow("dst",1); cvShowImage("src",pSrc); //将二值图像转换成灰度，以便显示 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;}
