Paper Info
Title
A New Radical-Based Approach To Online Handwritten Chinese Character Recognition
Abstract
This paper proposes a new radical-based approach for online handwritten Chinese character recognition. The approach is novel in three respects: statistical classification of radicals, over-segmentation Of characters into candidate radicals, and lexicon-driven recognition of characters. Currently, we have applied the approach to Chinese characters of left-right structure and are extending to other structures. Preliminary results on a sample set of 4,284 characters consisting of 1,118 radicals demonstrate the superiority of the proposed approach.
Year
DOI
Venue
2008
10.1109/ICPR.2008.4761207
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6
Keywords
Field
DocType
image classification,accuracy,image segmentation,hidden markov models,statistical analysis,feature extraction,pattern recognition,handwriting recognition
Chinese characters,Character recognition,Pattern recognition,Computer science,Handwriting recognition,Image segmentation,Feature extraction,Natural language processing,Artificial intelligence,Contextual image classification,Statistical classification,Hidden Markov model
Conference
ISSN
Citations 
PageRank 
1051-4651
11
0.60
References 
Authors
9
2
Name
Order
Citations
PageRank
Long-long Ma1265.72
Cheng-Lin Liu24367239.75