The State of the Art in Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICDAR '97 Proceedings of the 4th 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
On-Line Cursive Kanji Character Recognition Using Stroke-Based Affine Transformation
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
An Integration of Online and Pseudo-Online Information for Cursive Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
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We found suitable direction-change features of the imaginary strokes in the pen-up state for on-line handwritten cursive character recognition. Our method simultaneously uses both directional features, otherwise known as off-line features, and direction-change features, which we designed as on-line features. The directionl features express where and in which direction each character's coordinates exist. The direction-change features express where and in which direction each direction of the character's coordinates change, and express where the circular parts of the character exist. These direction-change features express both written strokes in the pen-down state and unwritten imaginary strokes in the pen-up state. It is important to get suitable direction-change features when using this method. We tried to examine the influence on character recognition rates when changing the functions used to get each direction-change feature based on the imaginary stroke lengths. Then, we found that the best function is the function which puts no weight on the imaginary stroke lengths. The recognition rate for freely-written Japanese characters was improved from 82.37% to 86.32% by our new method using the best function as opposed to our old method using a function which gets each direction change feature in inverse proportion to the imaginary stroke lengths.