Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimized Method for Iranian Road Signs Detection and recognition system   Road sign recognition is one of the core technologies in Intelligent
Transport Systems. In the current study, a robust and real-time method is
presented to identify and detect the roads speed signs in road image in
different situations. In our proposed method, first, the connected components
are created in the main image using the edge detection and mathematical
morphology and the location of the road signs extracted by the geometric and
color data; then the letters are segmented and recognized by Multiclass Support
Vector Machine (SVMs) classifiers. Regarding that the geometric and color
features ate properly used in detection the location of the road signs, so it
is not sensitive to the distance and noise and has higher speed and efficiency.
In the result part, the proposed approach is applied on Iranian road speed sign
database and the detection and recognition accuracy rate achieved 98.66% and
100% respectively.

25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga