Vehicle type classification using data mining techniques

Publisher:
Springer
Publication Type:
Conference Proceeding
Citation:
The Era of Interactive Media, 2013, pp. 325 - 335
Issue Date:
2013-10-01
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© 2013 Springer Science+Business Media, LLC. All rights reserved. In this paper, we proposed a novel and accurate visual-based vehicle type classification system. The system builts up a classifier through applying Support Vector Machine with various features of vehicle image. We made three contributions here: first, we originally incorporated color of license plate in the classification system. Moreover, the vehicle front was measured accurately based on license plate localization and background-subtraction technique. Finally, type probabilities for every vehicle image were derived from eigenvectors rather than deciding vehicle type directly. Instead of calculating eigenvectors from the whole body images of vehicle in existing methods, our eigenvectors are calculated from vehicle front images. These improvements make our system more applicable and accurate. The experiments demonstrated our system performed well with very promising classification rate under different weather or lighting conditions.
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