Proceedings ArticleDOI
Online recognition of freely handwritten Japanese characters using directional feature densities
A. Kawamura,K. Yura,T. Hayama,Y. Hidai,T. Minamikawa,A. Tanaka,S. Masuda +6 more
- pp 183-186
TLDR
The authors propose an online handwritten Japanese character recognition method permitting both stroke number and stroke order variations, based on the pattern matching technique, which has achieved a good recognition rate, 91%, for 2965 freely written Japanese kanji characters.Abstract:
The authors propose an online handwritten Japanese character recognition method permitting both stroke number and stroke order variations. The method is based on the pattern matching technique. Matching is done by the multiple similarity method using directional feature densities, which are independent of both stroke number and stroke order. This method has achieved a good recognition rate, 91%, for 2965 freely written Japanese kanji characters. >read more
Citations
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'Online recognition of Chinese characters: the state-of-the-art
TL;DR: This paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s, in terms of pattern representation, character classification, learning/adaptation, and contextual processing.
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Character Recognition Systems: A Guide for Students and Practitioners
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Handwritten digit recognition: investigation of normalization and feature extraction techniques
TL;DR: A comparison of normalization functions shows that moment-based functions outperform the dimension-based ones and the aspect ratio mapping is influential and the comparison of feature vectors shows that the improved feature extraction strategies outperform their baseline counterparts.
Proceedings ArticleDOI
A study on the use of 8-directional features for online handwritten Chinese character recognition
Zhen-Long Bai,Qiang Huo +1 more
TL;DR: This paper presents a study of using 8-directional features for online handwritten Chinese character recognition, and extensive experiments on the task of recognizing 3755 level-1 Chinese characters in GB2312-80 standard are performed, confirming the effectiveness of the studied approach.
References
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Journal ArticleDOI
A nonlinear normalization method for handprinted Kanji character recognition—line density equalization
TL;DR: The line density in thespace is homogenized, the efficiency of utilization of the space is increased, and a stable normalization is obtained for partially irregular shape variations.
Book ChapterDOI
A Theory of Character Recognition by Pattern Matching Method
TL;DR: Character recognition is a categorizing process of unknown input pattern into one of known finite number of character categories and the similarity of input pattern is tested with the reference pattern of each category.