Fabio's profile - activity

Actually, it doesn't seem to improve the separation. Using a larger kernel, gives the same result as using more times a little one.

I have used different kind of kernel, in size and stencil, but I can't find a useful algorith which could be general.

I'll investigate to find a solution. Thank you for the help!!

To be thorough I attach my code: < IplImage* image_out=cvCreateImage(cvGetSize(image_in), IPL_DEPTH_8U, 1);

  IplConvKernel* element_ell = cvCreateStructuringElementEx(3,3,0,0,CV_SHAPE_ELLIPSE,NULL);
  IplConvKernel* element_rect = cvCreateStructuringElementEx(3,3,0,0,CV_SHAPE_RECT,NULL);

   cvDilate(image_in,image_out,element_ell,1); ...

>

I have tried to use these operators without success. Using more than one time the same operator, such as cvDilate, it could separate the objects only when I have lost all the object's structure. I can show you which is the effect of this approach:

Using 6 times cvDilate with CV_SHAPE_RECT: https://dl.dropboxusercontent.com/u/522026/foto/rect/elab_six_rect.jpg

Using 6 times cvDilate with CV_SHAPE_ELLIPSE (which can better keep the round shape): https://dl.dropboxusercontent.com/u/522026/foto/ell/elab_six_ell.jpg

Hi to all, I'm a beginner of OpenCV and I'm doing a little project for my study. After a binarization, I need to separate object which are connected. I have tried using erosion o dilatation, but these operators seem inappropriate for the purpose.

Do you have any suggestion?

This is the image which I need to use. https://dl.dropboxusercontent.com/u/522026/foto/elaborated.jpg