Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatic skin lesion segmentation on dermoscopic images by the means of
  superpixel merging   We present a superpixel-based strategy for segmenting skin lesion on
dermoscopic images. The segmentation is carried out by over-segmenting the
original image using the SLIC algorithm, and then merge the resulting
superpixels into two regions: healthy skin and lesion. The mean RGB color of
each superpixel was used as merging criterion. The presented method is capable
of dealing with segmentation problems commonly found in dermoscopic images such
as hair removal, oil bubbles, changes in illumination, and reflections images
without any additional steps. The method was evaluated on the PH2 and ISIC 2017
dataset with results comparable to the state-of-art.

16
The categories of this paper are: stat
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an