Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A proposition of a robust system for historical document images
  indexation   Characterizing noisy or ancient documents is a challenging problem up to now.
Many techniques have been done in order to effectuate feature extraction and
image indexation for such documents. Global approaches are in general less
robust and exact than local approaches. That's why, we propose in this paper, a
hybrid system based on global approach(fractal dimension), and a local one
based on SIFT descriptor. The Scale Invariant Feature Transform seems to do
well with our application since it's rotation invariant and relatively robust
to changing illumination.In the first step the calculation of fractal dimension
is applied to images in order to eliminate images which have distant features
than image request characteristics. Next, the SIFT is applied to show which
images match well the request. However the average matching time using the
hybrid approach is better than "fractal dimension" and "SIFT descriptor" if
they are used alone.

11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio