Application of vision models to traffic sign recognition
Conference item
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2004. Application of vision models to traffic sign recognition. Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. (ed.) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Istanbul, Turkey 26 - 29 Sep 2003 Berlin, Heidelberg Springer. https://doi.org/10.1007/3-540-44989-2_131
Title | Application of vision models to traffic sign recognition |
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Authors | Gao, X., Shaposhnikov, D. and Podladchikova, L. |
Abstract | This paper extends earlier work on a vision behaviour model, FOSTS, which had been developed to perform the task of recognition of traffic signs. This work pioneered the application of a colour appearance model, CIECAM, developed theoretically for segmentation, which shows great advantages over other existing approaches. Much of the work was undertaken via a Royal Society funded scientific exchange programme, and has led to further collaborations internationally on a networking project on Tele-imaging in Medicine (TIME) funded by EU (CN/ASIA-IT&C/009(91450)). |
Research Group | Artificial Intelligence group |
Conference | Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 |
Proceedings Title | Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003: Joint International Conference ICANN/ICONIP 2003, Istanbul, Turkey, June 26–29, 2003, Proceedings |
Series | Lecture Notes in Computer Science |
Editors | Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. |
ISSN | 0302-9743 |
Electronic | 1611-3349 |
ISBN | |
Paperback | 9783540404088 |
Electronic | 9783540449898 |
Publisher | Springer |
Place of publication | Berlin, Heidelberg |
Publication dates | |
19 Feb 2004 | |
Publication process dates | |
Deposited | 15 Oct 2008 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1007/3-540-44989-2_131 |
Scopus EID | 2-s2.0-35248898305 |
Web of Science identifier | WOS:000185378100131 |
Web address (URL) of conference proceedings | https://doi.org/10.1007/3-540-44989-2 |
Language | English |
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