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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

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  • $\begingroup$ 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
    Commented Dec 23, 2014 at 10:57

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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.

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  • $\begingroup$ 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
    Commented Dec 26, 2014 at 22:39
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You can try grabcut algorithm. Check this link: Interactive Foreground Extraction using GrabCut Algorithm

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  • $\begingroup$ 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
    Commented Dec 25, 2014 at 2:04

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