DocumentCode
2860541
Title
A Novel Approach for License Plate Character Segmentation
Author
Yang, Feng ; Ma, Zheng ; Xie, Mei
Author_Institution
Sch. of Commun. & Information Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
fYear
2006
fDate
24-26 May 2006
Firstpage
1
Lastpage
6
Abstract
Character segmentation is an important step in license plate recognition (LPR) system. In this paper, a novel character segmentation method of license plate is presented combining Laplacian transformation, region growing and prior knowledge of license plate. In the proposed methodology, image preprocessing is performed to the license plate at first, and the character region in license plate is enhanced. Then the edges of the characters are detected by using Laplacian transformation and the candidate regions of characters are located by using region growing algorithm. And the character segmentation regions are determined by using prior knowledge of license plate. Finally the characters are segmented from original license plate and binarization is performed to the characters, which can make it more efficient for character recognition in OCR system. The proposed method in character segmentation is fast and accurate, and is tolerant to license plate with deformations, rotations, plate frame, rivet, the space mark, and so on. And promising results have been obtained in experiments on Chinese license plates
Keywords
Laplace transforms; character recognition; edge detection; image segmentation; Chinese license plates; Laplacian transformation; character binarization; character edge detection; license plate character segmentation; license plate recognition system; region growing; Character recognition; Image edge detection; Image segmentation; Laplace equations; Licenses; Optical character recognition software; Robustness; Statistics; Surveillance; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2006 1ST IEEE Conference on
Conference_Location
Singapore
Print_ISBN
0-7803-9513-1
Electronic_ISBN
0-7803-9514-X
Type
conf
DOI
10.1109/ICIEA.2006.257234
Filename
4025835
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