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Tifinagh Character Recognition Using Geodesic Distances, Decision Trees & Neural Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bencharef, Omar Fakir, Mohammed Minaoui, Brahim Bouikhalene, Belaid |
| Copyright Year | 2011 |
| Abstract | The recognition of Tifinagh characters cannot be perfectly carried out using the conventional methods which are based on the invariance, this is due to the similarity that exists between some characters which differ from each other only by size or rotation, hence the need to come up with new methods to remedy this shortage. In this paper we propose a direct method based on the calculation of what is called Geodesic Descriptors which have shown significant reliability vis-a-vis the change of scale, noise presence and geometric distortions. For classification, we have opted for a method based on the hybridization of decision trees and neural networks. |
| File Format | PDF HTM / HTML |
| DOI | 10.14569/SpecialIssue.2011.010308 |
| Volume Number | 1 |
| Alternate Webpage(s) | http://thesai.org/Downloads/SpecialIssueNo3/Paper%208-Tifinagh%20Character%20Recognition%20Using%20Geodesic%20Distances%20Decision%20Trees%20Neural%20Networks.pdf |
| Alternate Webpage(s) | https://doi.org/10.14569/SpecialIssue.2011.010308 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
