Evaluating automatic road detection across a large aerial imagery collection
| Data(s) |
07/12/2011
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|---|---|
| Resumo |
The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features. |
| Formato |
application/pdf application/pdf |
| Identificador | |
| Publicador |
IEEE |
| Relação |
http://eprints.qut.edu.au/47715/1/DICTA2011.pdf http://eprints.qut.edu.au/47715/2/DICTA2011_slides.pdf http://itee.uq.edu.au/~dicta2011/ Guo, Xufeng, Dean, David B., Denman, Simon, Fookes, Clinton B., & Sridharan, Sridha (2011) Evaluating automatic road detection across a large aerial imagery collection. In Proceedings of the 2011 International Conference of Digital Image Computing: Techniques and Applications, IEEE, Sheraton Noosa Resort & Spa, Noosa, QLD, pp. 140-145. |
| Direitos |
Copyright 2011 IEEE Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Fonte |
Faculty of Built Environment and Engineering; Information Security Institute; School of Engineering Systems |
| Palavras-Chave | #080106 Image Processing #Automatic Road Detection #Database |
| Tipo |
Conference Paper |
