文章基本信息

标题：Best Combination of Binarization Methods for License Plate Character Segmentation
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作者：Yoon, Youngwoo ; Ban, Kyu-Dae ; Yoon, Hosub 等
期刊名称：ETRI Journal
印刷版ISSN：1225-6463
电子版ISSN：2233-7326
出版年度：2013
卷号：35
期号：3
页码：491-500
DOI：10.4218/etrij.13.0112.0545
语种：English
出版社：Electronics and Telecommunications Research Institute
摘要：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.
关键词：Character segmentation;binarization;binary image;automatic license plate recognition