Identify Handwriting Individually Using Feed Forward Neural Networks
| Autor: | Constantin Anton, Cosmin Stirbu, Romeo-Vasile Badea |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Modality (human–computer interaction)
Biometrics business.industry Computer science Speech recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Feed forward neural Sample (statistics) computer.software_genre Field (computer science) Identification (information) Direct applicability Handwriting Artificial intelligence business computer Natural language processing |
| Zdroj: | International Journal of Intelligent Computing Research. 2:169-174 |
| ISSN: | 2042-4655 |
| DOI: | 10.20533/ijicr.2042.4655.2011.0022 |
| Popis: | The paper justifies the necessity to use the hand writer identification using the feed forward neural networks. Identifying the authors of a handwritten sample using automatic image-based processing methods is an interesting pattern recognition problem with direct applicability in the legal and historic documents. Leading a worrisome life among the harder forms of biometrics, the identification of a writer on the basis of handwriting samples still remains a useful biometric modality, mainly due to its applicability in historical and the forensic field. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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