Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient IRIS Recognition through Improvement of Feature Extraction and
  subset Selection   The selection of the optimal feature subset and the classification has become
an important issue in the field of iris recognition. In this paper we propose
several methods for iris feature subset selection and vector creation. The
deterministic feature sequence is extracted from the iris image by using the
contourlet transform technique. Contourlet transform captures the intrinsic
geometrical structures of iris image. It decomposes the iris image into a set
of directional sub-bands with texture details captured in different
orientations at various scales so for reducing the feature vector dimensions we
use the method for extract only significant bit and information from normalized
iris images. In this method we ignore fragile bits. And finally we use SVM
(Support Vector Machine) classifier for approximating the amount of people
identification in our proposed system. Experimental result show that most
proposed method reduces processing time and increase the classification
accuracy and also the iris feature vector length is much smaller versus the
other methods.

3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg