ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Off-line Character Recognition using On-line Character Writing Information
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
On-line Overlaid-Handwriting Recognition Based on Substroke HMMs
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
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Online Character Recognition Based on Elastic Matching and Quadratic Discrimination
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Online Handwritten Shape Recognition Using Segmental Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recent results of online Japanese handwriting recognition and its applications
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Semi-synchronous speech and pen input for mobile user interfaces
Speech Communication
Reconstructing the correct writing sequence from a set of chinese character strokes
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Adaptive online multi-stroke sketch recognition based on hidden markov model
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Painting in the air with Wii Remote
Expert Systems with Applications: An International Journal
Lightweight user-adaptive handwriting recognizer for resource constrained handheld devices
Proceeding of the workshop on Document Analysis and Recognition
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Abstract: A new method is proposed for on-line handwriting recognition of Kanji characters. The method employs substroke HMMs as minimum units to constitute Japanese Kanji characters and utilizes the direction of pen motion. The main motivation is to fully utilize the continuous speech recognition algorithm by relating sentence speech to Kanji character, phonemes to substrokes, and grammar to Kanji structure. The proposed system consists input feature analysis, substroke HMMs, a character structure dictionary and a decoder. The present approach has the following advantages over the conventional methods that employ whole character HMMs. 1) Much smaller memory requirement for dictionary and models. 2) Fast recognition by employing efficient substroke network search. 3) Capability of recognizing characters not included in the training data if defined as a sequence of substrokes in the dictionary. 4) Capability of recognizing characters written by various different stroke orders with multiple definitions per one character in the dictionary. 5) Easiness in HMM adaptation to the user with a few sample character data.