Vector quantization and signal compression
Vector quantization and signal compression
Markov random field modeling in image analysis
Markov random field modeling in image analysis
SSPR '96 Proceedings of the 6th International Workshop on Advances in Structural and Syntactical Pattern 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
Pen Pressure Features for Writer-Independent On-Line Handwriting Recognition Based on Substroke HMM
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Binarization of Low Quality Text Using a Markov Random Field Model
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Context-Dependent Substroke Model for HMM-Based On-Line Handwriting Recognition
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Substroke Approach to HMM-Based On-line Kanji Handwriting Recognition
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Online Recognition of Chinese Characters: The State-of-the-Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Collection of on-line handwritten Japanese character pattern databases and their analyses
International Journal on Document Analysis and Recognition
Markov Random Fields for Handwritten Chinese Character Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
An Efficient Radical-Based Algorithm for Stroke-Order-Free Online Kanji Character Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Minimum Error Discriminative Training for Radical-Based Online Chinese Handwriting Recognition
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
A robust model for on-line handwritten japanese text recognition
International Journal on Document Analysis and Recognition - Special Issue DRR09
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
ICFHR '10 Proceedings of the 2010 12th International Conference on Frontiers in Handwriting Recognition
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
International Journal on Document Analysis and Recognition - Special issue - Selected and extended papers from ICDAR2009
ICFHR '12 Proceedings of the 2012 International Conference on Frontiers in Handwriting Recognition
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This paper describes a method for building a compact online Markov random field (MRF) recognizer for large handwritten Japanese character set using structured dictionary representation and vector quantization (VQ) technique. The method splits character patterns into radicals, whose models by MRF are shared by different character classes such that a character model is constructed from the constituent radical models. Many distinct radicals are shared by many character classes with the result that the storage space of model dictionary can be saved. Moreover, in order to further compress the parameters, VQ technique to cluster parameter sequences of the mean vectors and covariance matrixes for MRF unary features and binary features as well as the transition probabilities of each state into groups was employed. By sharing a common parameter sequence for each group, the dictionary of the MRF recognizer can be greatly compressed without recognition accuracy loss.