상세정보
학술지
Best Combination of Binarization Methods for License Plate Character Segmentation
- 발행일
- 201306
- 출처
- ETRI Journal, v.35 no.3, pp.491-500
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 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.
- KSP 제안 키워드
- Carry out, Connected component analysis, Experiment results, In-depth analysis, Uneven Illumination, binary image, image noise, license plate character segmentation, quantitative evaluation, segmentation method