An HMM implementation for on-line handwriting recognition based on pen-coordinate feature and pen-direction feature
| Autor: | D. Okumura, Hiroaki Sakoe, Seiichi Uchida |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Computer science
Intelligent character recognition business.industry Speech recognition Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition ComputingMethodologies_PATTERNRECOGNITION Line segment Computer Science::Sound Feature (computer vision) Position (vector) Handwriting recognition Line (geometry) Feature (machine learning) Artificial intelligence Hidden Markov model business |
| Zdroj: | ICDAR |
| DOI: | 10.1109/icdar.2005.50 |
| Popis: | An on-line handwritten character recognition technique based on a new HMM is proposed. In the proposed HMM, not only pen-direction feature but also pen-coordinate feature are separately utilized for describing the shape variation of on-line characters accurately. Specifically speaking, the proposed HMM outputs a pen-coordinate feature at each inter-state transition and outputs a pen-direction feature at each intra-state transition, i.e., self-transition. Thus, each state of the proposed HMM can specify the starting position and the direction of a line segment by its incoming inter-state transition and intra-state transition, respectively. The results of recognition experiments on 10-stroke Chinese characters show that the proposed HMM outperforms the conventional HMM which does not use the pen-coordinate feature because of its non-stationarity. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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