Volume: 17, Issue: 1, November
2013
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Speed Sign Recognition using Independent Component
Analysis
Authors: Ayman M Mansour, Jafar
Abukhait, Imad Zyout
Abstract:
This paper
proposes a system for speed limit signs recognition in the United States. The
proposed system is based on Independent Component Analysis (ICA). Our proposed system can be used in driver
assistant system (DAS) or autonomous vehicles. The proposed system consists
of four stages: 1) color segmentation to remove non-speed sign objects from
the scene; 2) speed sign shape detection and recognition using geometric
means; 3) Representation of speed sign images using Independent Component
Analysis (ICA) ; 4) feature extraction and classification of speed sign
images. The proposed system is invariant to scale, rotation, and partial
occlusion. Independent Component Analysis (ICA) has been used in this paper
to capture the inherent properties of the speed signs in order to be
recognized. This was done by creating an independent component bank (or can
be called as basis function bank) from a training set of speed signs. Feature
vectors are generated from IC’s bank which is used for recognizing speed signs
in the testing stage. Our experimental results show a significant recognition
accuracy rate of rectangular speed signs.
(pp. 832-838)
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