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학술지 Best Combination of Binarization Methods for License Plate Character Segmentation
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저자
윤영우, 반규대, 윤호섭, 이재연, 김재홍
발행일
201306
출처
ETRI Journal, v.35 no.3, pp.491-500
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.13.0112.0545
협약과제
11SF1100, 시각 생체 모방 소자 및 인지 시스템 기술 개발, 정명애
초록
A connected component analysis from a binary image is a popular character segmentation method but occasionally fails to segment the characters owing to image noise and uneven illumination. A multimethod binarization scheme that incorporates two or more binary images is a novel solution, but selection of binarization methods has never been analyzed before. This paper reveals the best combination of binarization methods and parameters and presents an in-depth analysis of the multimethod binarization scheme for better character segmentation. We carry out an extensive quantitative evaluation, which shows a significant improvement over conventional single-method binarization methods. Experiment results of six binarization methods and their combinations with different test images are presented. © 2013 ETRI.
키워드
Automatic license plate recognition, Binarization, Binary image, Character segmentation
KSP 제안 키워드
Automatic license plate recognition(ALPR), Carry out, Connected component analysis, Experiment results, In-depth analysis, Uneven Illumination, binary image, image noise, license plate character segmentation, quantitative evaluation, segmentation method