DocumentCode :
2146162
Title :
Look Inside the World of Parts of Handwritten Characters
Author :
Song, Wang ; Uchida, Seiichi ; Liwicki, Marcus
Author_Institution :
Kyushu Univ., Fukuoka, Japan
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
784
Lastpage :
788
Abstract :
Part-based recognition is expected to be robust in difficult handwritten character recognition tasks. This is because part-based recognition is based on aggregation of independent recognition results at individual local parts without considering their global relations and thus is robust against various deformations, such as partial occlusion, overlap, broken stroke, etc. Since part-based recognition is a new approach, there are still several open problems toward its practical use. For example, compared with entire images, local parts are more ambiguous, i.e., less discriminative. For better recognition accuracy and less computations, we need to know the characteristics of local parts and then, for example, discard less discriminative parts. The purpose of this paper is to conduct some experiments in order to observe and analyze how the local parts of multiple classes are distributed in feature spaces. By handling parts appropriately based on the analysis, we will be able to enhance the usefulness of the part-based method.
Keywords :
handwritten character recognition; broken stroke; feature spaces; handwritten character recognition tasks; overlap; part-based recognition; partial occlusion; Accuracy; Character recognition; Databases; Handwriting recognition; Image recognition; Robustness; Training; distribution; handwritten character recognition; local features; part-based recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.161
Filename :
6065418
Link To Document :
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