DocumentCode :
3537267
Title :
Binarization of Degraded Characters Using Tensor Voting Based Color Clustering
Author :
Madhubalan, Kavitha ; Lee, Gueesang
Author_Institution :
Dept. of Electron. & Comput. Eng., Chonnam Nat. Univ., Gwangju, South Korea
fYear :
2011
fDate :
Aug. 31 2011-Sept. 2 2011
Firstpage :
299
Lastpage :
305
Abstract :
In this paper, a new method of binarizing degraded characters from scene images is presented. The proposed method helps in obtaining a binarized result even with multicolored characters subjected to heavy degradation. Color information is used in the proposed binarization method to help to separate the character from the image background and to obtain a clean representation of the final result. Images from the ICDAR 2003 robust character recognition database are used to compare the effectiveness and accuracy of the proposed algorithm with other methods.
Keywords :
character recognition; image colour analysis; image representation; pattern clustering; ICDAR 2003 robust character recognition database; character separation; color clustering; degraded character binarization; image background; image representation; multicolored characters; tensor voting; Clustering algorithms; Colored noise; Feature extraction; Image color analysis; Lighting; Tensile stress; Tensor voting; color image segmentation; scene text recognition; text binarization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on
Conference_Location :
Pafos
Print_ISBN :
978-1-4577-0383-6
Electronic_ISBN :
978-0-7695-4388-8
Type :
conf
DOI :
10.1109/CIT.2011.55
Filename :
6036777
Link To Document :
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