thinning&&opencv 

  1 #include "opencv/cxcore.h"
  2 #include "opencv/cv.h"
  3 #include "opencv/highgui.h"
  4 /**************************************************************************
  5 函数：void cvThin( IplImage* src, IplImage* dst, int iterations=1)
  6 功能：将IPL_DEPTH_8U型二值图像进行细化
  7 参数：
  8 src，原始IPL_DEPTH_8U型二值图像
  9 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
 10 iterations，迭代次数
 11 *************************************************************************/
 12 void cvThin( IplImage* src, IplImage* dst, int iterations=1)
 13 {
 14  CvSize size = cvGetSize(src);
 15 
 16  cvCopy(src, dst);
 17     int n = 0,i = 0,j = 0;
 18  for(n=0; n<iterations; n++)
 19  {
 20   IplImage* t_image = cvCloneImage(dst);
 21   for(i=0; i<size.height;  i++)
 22   {
 23    for(j=0; j<size.width; j++)
 24    {
 25     if(CV_IMAGE_ELEM(t_image,uchar,i,j)==1)
 26     {
 27      int ap=0;
 28      int p2 = (i==0)?0:CV_IMAGE_ELEM(t_image,uchar, i-1, j);
 29      int p3 = (i==0 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar, i-1, j+1);
 30      if (p2==0 && p3==1)
 31      {
 32       ap++;
 33      }
 34      int p4 = (j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar,i,j+1);
 35      if(p3==0 && p4==1)
 36      {
 37       ap++;
 38      }
 39      int p5 = (i==size.height-1 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j+1);
 40      if(p4==0 && p5==1)
 41      {
 42       ap++;
 43      }
 44      int p6 = (i==size.height-1)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j);
 45      if(p5==0 && p6==1)
 46      {
 47       ap++;
 48      }
 49      int p7 = (i==size.height-1 || j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j-1);
 50      if(p6==0 && p7==1)
 51      {
 52       ap++;
 53      }
 54      int p8 = (j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i,j-1);
 55      if(p7==0 && p8==1)
 56      {
 57       ap++;
 58      }
 59      int p9 = (i==0 || j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i-1,j-1);
 60      if(p8==0 && p9==1)
 61      {
 62       ap++;
 63      }
 64      if(p9==0 && p2==1)
 65      {
 66       ap++;
 67      }
 68      if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7)
 69      {
 70       if(ap==1)
 71       {
 72        if(!(p2 && p4 && p6))
 73        {
 74         if(!(p4 && p6 && p8)) 
 75         {
 76          CV_IMAGE_ELEM(dst,uchar,i,j)=0;
 77         }
 78        }
 79       }
 80      }
 81 
 82     }
 83    }
 84   }
 85   cvReleaseImage(&t_image);
 86   t_image = cvCloneImage(dst);
 87   for(i=0; i<size.height;  i++)
 88   {
 89    for(int j=0; j<size.width; j++)
 90    {
 91     if(CV_IMAGE_ELEM(t_image,uchar,i,j)==1)
 92     {
 93      int ap=0;
 94      int p2 = (i==0)?0:CV_IMAGE_ELEM(t_image,uchar, i-1, j);
 95      int p3 = (i==0 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar, i-1, j+1);
 96      if (p2==0 && p3==1)
 97      {
 98       ap++;
 99      }
100      int p4 = (j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar,i,j+1);
101      if(p3==0 && p4==1)
102      {
103       ap++;
104      }
105      int p5 = (i==size.height-1 || j==size.width-1)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j+1);
106      if(p4==0 && p5==1)
107      {
108       ap++;
109      }
110      int p6 = (i==size.height-1)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j);
111      if(p5==0 && p6==1)
112      {
113       ap++;
114      }
115      int p7 = (i==size.height-1 || j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i+1,j-1);
116      if(p6==0 && p7==1)
117      {
118       ap++;
119      }
120      int p8 = (j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i,j-1);
121      if(p7==0 && p8==1)
122      {
123       ap++;
124      }
125      int p9 = (i==0 || j==0)?0:CV_IMAGE_ELEM(t_image,uchar,i-1,j-1);
126      if(p8==0 && p9==1)
127      {
128       ap++;
129      }
130      if(p9==0 && p2==1)
131      {
132       ap++;
133      }
134      if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7)
135      {
136       if(ap==1)
137       {
138        if(p2*p4*p8==0)
139        {
140         if(p2*p6*p8==0)
141         {
142          CV_IMAGE_ELEM(dst, uchar,i,j)=0;
143         }
144        }
145       }
146      }                    
147     }
148 
149    }
150 
151   }            
152   cvReleaseImage(&t_image);
153  }
154 
155 }
156 
157 
158  
159 
160 int main(int argc, char* argv[])
161 {
162  if(argc!=2)
163  {
164   return 0;
165  }
166  IplImage *pSrc = NULL,*pDst = NULL,*pTmp = NULL;
167 
168 //传入一个灰度图像
169  pSrc = cvLoadImage(argv[1],CV_LOAD_IMAGE_GRAYSCALE);
170  if(!pSrc)
171  {
172   return 0;
173  }
174  pTmp = cvCloneImage(pSrc);
175     pDst = cvCreateImage(cvGetSize(pSrc),pSrc->depth,pSrc->nChannels);
176  cvZero(pDst);
177  cvThreshold(pSrc,pTmp,128,1,CV_THRESH_BINARY_INV);//做二值处理，将图像转换成0，1格式
178  //cvSaveImage("c://Threshold.bmp",pTmp,0);
179  cvThin(pTmp,pDst,8);//细化，通过修改iterations参数进一步细化
180  cvNamedWindow("src",1);
181  cvNamedWindow("dst",1);
182  cvShowImage("src",pSrc);
183  //将二值图像转换成灰度，以便显示
184  int i = 0,j = 0;
185  CvSize size = cvGetSize(pDst);
186  for(i=0; i<size.height;  i++)
187  {
188   for(j=0; j<size.width; j++)
189   {
190    if(CV_IMAGE_ELEM(pDst,uchar,i,j)==1)
191    {
192     CV_IMAGE_ELEM(pDst,uchar,i,j) = 0;
193    }
194    else
195    {
196     CV_IMAGE_ELEM(pDst,uchar,i,j) = 255;
197    }
198   }
199  }
200  //cvSaveImage("c://thin.bmp",pDst);
201  cvShowImage("dst",pDst);
202  cvWaitKey(0);
203     cvReleaseImage(&pSrc);
204  cvReleaseImage(&pDst);
205  cvReleaseImage(&pTmp);
206  cvDestroyWindow("src");
207  cvDestroyWindow("dst");
208  return 0;
209 }
示例代码

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。

 

关于图像细化的算法可以参看下面两个PDF链接：

http://www.uel.br/pessoal/josealexandre/stuff/thinning/ftp/lam-lee-survey.pdf  ：总结了几乎所有92年以前的经典细化算法

http://www-prima.inrialpes.fr/perso/Tran/Draft/gateway.cfm.pdf ：本文所附代码所参照的算法

posted on 2014-05-13 16:13  vincent_SK  阅读(443)  评论(0)  编辑  收藏  举报