전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제65권1호
  • /
  • Pages.142-149
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  • 2016
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  • 1975-8359(pISSN)
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  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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차량 번호판 인식을 위한 앙상블 학습기 기반의 최적 특징 선택 방법

An Ensemble Classifier Based Method to Select Optimal Image Features for License Plate Recognition

  • Jo, Jae-Ho (School of Mechanical Engineering, Pusan National University) ;
  • Kang, Dong-Joong (School of Mechanical Engineering, Pusan National University)
  • 투고 : 2015.11.13
  • 심사 : 2015.12.24
  • 발행 : 2016.01.01
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초록

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.

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참고문헌

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