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http://dx.doi.org/10.4218/etrij.13.0112.0545

Best Combination of Binarization Methods for License Plate Character Segmentation  

Yoon, Youngwoo (IT Convergence Technology Research Laboratory, ETRI)
Ban, Kyu-Dae (IT Convergence Technology Research Laboratory, ETRI)
Yoon, Hosub (IT Convergence Technology Research Laboratory, ETRI)
Lee, Jaeyeon (IT Convergence Technology Research Laboratory, ETRI)
Kim, Jaehong (IT Convergence Technology Research Laboratory, ETRI)
Publication Information
ETRI Journal / v.35, no.3, 2013 , pp. 491-500 More about this Journal
Abstract
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.
Keywords
Character segmentation; binarization; binary image; automatic license plate recognition;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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