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An Ensemble Classifier Based Method to Select Optimal Image Features for License Plate Recognition
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 Title & Authors
An Ensemble Classifier Based Method to Select Optimal Image Features for License Plate Recognition
Jo, Jae-Ho; Kang, Dong-Joong;
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 Abstract
This paper proposes a method to detect LP(License Plate) of vehicles in indoor and outdoor parking lots. In restricted environment, there are many conventional methods for detecting LP. But, it is difficult to detect LP in natural and complex scenes with background clutters because several patterns similar with text or LP always exist in complicated backgrounds. To verify the performance of LP text detection in natural images, we apply MB-LGP feature by combining with ensemble machine learning algorithm in purpose of selecting optimal features of small number in huge pool. The feature selection is performed by adaptive boosting algorithm that shows great performance in minimum false positive detection ratio and in computing time when combined with cascade approach. MSER is used to provide initial text regions of vehicle LP. Throughout the experiment using real images, the proposed method functions robustly extracting LP in natural scene as well as the controlled environment.
 Keywords
License plate number extraction;Maximally stable extremal regions(MSER);Multi-block local gradient patterns(MB-LGP);
 Language
Korean
 Cited by
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