상세정보
학술대회
Number Detection in Natural Image with Boosting Classifier
- 발행일
- 201211
- 출처
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2012, pp.525-526
- 협약과제
- 12VC1800, 인식센서융합 기반 실환경하에서 임의의 사용자 30명에 대해 인식률 99%에 근접하는 사용자의 신원과 행위 및 위치 정보 인식 기술 개발, 윤호섭
- 초록
- The number detection is useful in various applications such as license plate localization, detection of number button in elevator, and detection of exit number sign in public transport station. In this paper, we propose number detection methods in natural image using AdaBoost based on Modified Census Transform (MCT) features. It is a difficult task to detect numbers, characters, and specific symbols, because natural image includes many noises. Especially, illumination change is one of the most annoying sources of noise in the field of number detection based on image processing. Our number detection method uses many MCT features, which are robust to illumination change and AdaBoost for the feature selection to overcome this restriction. Experimental results show that the proposed method has a high detection rate in our license plate database which has been captured in the natural environment. Copyright © 2012 IEEE.
- KSP 제안 키워드
- Census Transform, Detection Method, Feature selection(FS), Illumination change, Image processing, Natural environment, Public transport, Transport station, boosting classifier, detection rate(DR), license plate