thinningopencv
2024-06-11 02:43:02
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
转载于:https://www.cnblogs.com/fandaojian/p/3725785.html
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