DocumentCode :
183317
Title :
Large Improvement in Line-Direction-Free and Character-Orientation-Free On-Line Handwritten Japanese Text Recognition
Author :
Yuechan Hao ; Bilan Zhu ; Nakagawa, Masaki
Author_Institution :
Tokyo Univ. of Agric. & Technol., Koganei, Japan
fYear :
2014
fDate :
1-4 Sept. 2014
Firstpage :
329
Lastpage :
334
Abstract :
This paper describes significant improvement in On-line handwritten Japanese text recognition that is free from line direction and character orientation constraints. The original system [1, 2] separates freely written text into text line elements, estimates and normalizes character orientation and line direction. Then, it hypothetically segments each text line element into primitive segments, constructs a segmentation-recognition candidate lattice and evaluates the likelihood of candidate segmentation-recognition paths by combining the scores of character recognition, geometric features, as well as linguistic context. In this scheme, we have updated the over-segmentation for each text line element and applied a robust context integration model to recognize each text line element. Experimental results on text from the HANDS-Kondate_t_bf-2001-11 database demonstrate large improvement in the character recognition rate compared with the previous system [1, 2].
Keywords :
feature extraction; handwritten character recognition; image segmentation; natural language processing; HANDS-Kondate_t_bf-2001-11 database; candidate segmentation-recognition path likelihood evaluation; character orientation constraint; character orientation normalization; character recognition; character-orientation-free online handwritten Japanese text recognition; context integration model; geometric features; line direction constraint; line direction normalization; line-direction-free online handwritten Japanese text recognition; linguistic context; over-segmentation; segmentation-recognition candidate lattice; text line element recognition; text line element segmentation; Abstracts; Character recognition; Estimation; Handwriting recognition; Support vector machines; Text recognition; On-line recognition; character recognition; handwriting recognition; text recognition; writing constraints;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on
Conference_Location :
Heraklion
ISSN :
2167-6445
Print_ISBN :
978-1-4799-4335-7
Type :
conf
DOI :
10.1109/ICFHR.2014.62
Filename :
6981041
Link To Document :
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