Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Information Processing
The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM Based On-Line Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast HMM Algorithm for On-line Handwritten Character Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Hybrid Pen-Input Character Recognition System Based on Integration of Online-Offline Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Robust and Highly Customizable Recognition of On-Line Handwritten Japanese Characters
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
A Formulation of Learning Vector Quantization Using a New Misclassification Measure
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
A Maximum-Likelihood Approach to Segmentation-Based Recognition of Unconstrained Handwriting Text
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Substroke Approach to HMM-Based On-line Kanji Handwriting Recognition
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Bayesian Network Modeling of Hangul Characters for On-line Handwriting Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Combining Online and Offline Handwriting Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Formalization of On-line Handwritten Japanese Text Recognition free from Line Direction Constraint
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Collection of on-line handwritten Japanese character pattern databases and their analyses
International Journal on Document Analysis and Recognition
A Search Method for On-Line Handwritten Text Employing Writing-Box-Free Handwriting Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Pen-Coordinate Information Modeling by SCPR-based HMM for On-line Japanese Handwriting Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
IEICE - Transactions on Information and Systems
International Journal on Document Analysis and Recognition
Segmentation of on-line handwritten japanese text using SVM for improving text recognition
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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This paper discusses online handwriting recognition of Japanese characters, a mixture of ideographic characters (Kanji) of Chinese origin, and the phonetic characters made from them. Most Kanji character patterns are composed of multiple subpatterns, called radicals, which are shared among many (sometimes hundreds of) Kanji character patterns. This is common in Oriental languages of Chinese origin, i.e., Chinese, Korean and Japanese. It is also common that each language has thousands of characters. Given these characteristics, structured character pattern representation (SCPR) composed of subpatterns is effective in terms of the size reduction of a prototype dictionary (a set of prototype patterns) and the robustness to deformation of common subpatterns. In this paper, we show a prototype learning algorithm and HMM-based recognition for SCPR. Then, we combine the SCPR-based online recognizer with a compact offline recognizer employing quadratic discriminant functions. Moreover, we also discuss online handwritten Japanese text recognition and propose character orientation-free and line direction-free handwritten text recognition and segmentation. Finally, as applications of online handwritten Japanese text recognition, we show segmentation of mixed objects of text, formulas, tables and line-drawings, and handwritten text search.