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