1
$\begingroup$

I've been given an image from Berkeley dataset to segmentate. I am an undergrad student and so far I threw everything i know to this thing. But the colors are extremely close. I tried;

  • Clustering
  • Edge Detection
  • Histogram Thresholding

I need suggestions. Which path should I take? I need to segmentate the animals from this picture but I was only able to remove the green leafs.

enter image description here

$\endgroup$
  • $\begingroup$ You should consider reading some kind of survey of methods. That is what I do when I start working on something new $\endgroup$ – Andrey Rubshtein Dec 23 '14 at 10:57
0
$\begingroup$

Take a look at SLICO : http://infoscience.epfl.ch/record/177415 .

Superpixels along with graphcut/grabcut methods are quite good at similar segmentation problems. I have had really good results with SLICO and MRFs/Simulated Annealing approaches.

$\endgroup$
  • $\begingroup$ SLIC was quite useful thank you. I used Peter Kovesi's article and applied SLIC, afterwards I applied DBSCAN clustering for merging superpixels together. $\endgroup$ – Mert Çelikok Dec 26 '14 at 22:39
0
$\begingroup$

You can try grabcut algorithm. Check this link: Interactive Foreground Extraction using GrabCut Algorithm

$\endgroup$
  • $\begingroup$ Thanks for your answer. This is also an algorithm i would like to try and Berkeley's website states graphcut algorithms work well with this image. But I applied SLIC + DBScan so that's why I accepted Ameya005's answer. $\endgroup$ – Mert Çelikok Dec 25 '14 at 2:04

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.