Unsupervised writer adaptation applied to handwritten text recognition
| Autor: | Laurent Heutte, A. Nosary, Thierry Paquet |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Computer science
Intelligent character recognition business.industry Speech recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION computer.software_genre Document processing Intelligent word recognition ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Handwriting Signal Processing Word recognition ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Feature (machine learning) Computer Vision and Pattern Recognition Artificial intelligence Adaptation (computer science) business computer Software Natural language processing Word (computer architecture) |
| Zdroj: | Pattern Recognition. 37:385-388 |
| ISSN: | 0031-3203 |
| DOI: | 10.1016/s0031-3203(03)00185-7 |
| Popis: | This paper deals with the problem of off-line handwritten text recognition. It presents a system of text recognition that exploits an original principle of adaptation to the handwriting to be recognized. The adaptation principle is based on the automatic learning, during the recognition, of the graphical characteristics of the handwriting. This on-line adaptation of the recognition system relies on the iteration of two steps: a word recognition step that allows to label the writer's representations (allographs) on the whole text and a re-evaluation step of character models. Tests carried out on a sample of 15 writers, all unknown by the system, show the interest of the proposed adaptation scheme since we obtain during iterations an improvement of recognition rates both at the letter and the word levels. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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