Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Segmentation and Classification of Skin Lesions for Disease Diagnosis   In this paper, a novel approach for automatic segmentation and classification
of skin lesions is proposed. Initially, skin images are filtered to remove
unwanted hairs and noise and then the segmentation process is carried out to
extract lesion areas. For segmentation, a region growing method is applied by
automatic initialization of seed points. The segmentation performance is
measured with different well known measures and the results are appreciable.
Subsequently, the extracted lesion areas are represented by color and texture
features. SVM and k-NN classifiers are used along with their fusion for the
classification using the extracted features. The performance of the system is
tested on our own dataset of 726 samples from 141 images consisting of 5
different classes of diseases. The results are very promising with 46.71% and
34% of F-measure using SVM and k-NN classifier respectively and with 61% of
F-measure for fusion of SVM and k-NN.

33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat