Representation of online handwriting using multi-component sinusoidal model
| Autor: | Himakshi Choudhury, S. R. Mahadeva Prasanna |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Pattern recognition Sinusoidal model 02 engineering and technology 01 natural sciences Artificial Intelligence Handwriting Handwriting recognition Computer Science::Computer Vision and Pattern Recognition Component (UML) 0103 physical sciences Signal Processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Point (geometry) Computer Vision and Pattern Recognition Artificial intelligence 010306 general physics Representation (mathematics) business Software |
| Zdroj: | Pattern Recognition. 91:200-215 |
| ISSN: | 0031-3203 |
| Popis: | The representation of online handwriting is an important aspect of handwriting applications, which involves the extraction of various spatial and temporal attributes for analysis and individualization of handwritten patterns. In this work, a model based representation is proposed for online handwriting using a multi-component sinusoidal model. The method extracts sinusoidal parameters from handwriting by modeling its horizontal and vertical velocities between each successive pair of zero crossing points with a half period of the sine function. Thus, each velocity profile is represented by the sinusoidal oscillations whose parameters are modulated at the zero-crossing points. The use of multiple oscillations to model the velocities results in a better representation of the complex trajectories. The parameters of the proposed model are computed iteratively from its residual signals. We hypothesize that the analysis of the sinusoidal components and its parameters may provide added dynamic information about the handwriting. The efficacy of the proposal is demonstrated for online signature representation and synthetic variability generation by modifying the extracted parameters. Further, the proposed feature set is also employed for online handwriting recognition task. It is observed that the multi-component sinusoidal representation combined with existing point-based features provide an improvement in the recognition performance. |
| Databáze: | OpenAIRE |
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