Abstract
This paper addresses the automatic analysis and segmentation of real-life traffic images aimed at providing the necessary and sufficient information for automatic car driving. The paper focuses on the basic task of segmenting the lane boundaries. As the general objective is to build a very robust segmentation module, able to cope with any kind of road and motorway and for any kind of surroundings and background, either rural or urban, we face a complex problem of texture analysis and classification which we have approached by applying the frequency histogram of connected elements (FHCE). To assure an efficient design of the segmentation module, a thorough experimentation with numerous traffic images has been undertaken. In particular, the optimum design of the crucial parameters of the FHCE (namely, the structurant morphological element, the connectivity level and the scanning window) has been carried out with special care. Experimental results are finally presented and discussed.
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Patricio, M.Á., Maravall, D. (2003). Segmentation of Traffic Images for Automatic Car Driving. In: Moreno-Díaz, R., Pichler, F. (eds) Computer Aided Systems Theory - EUROCAST 2003. EUROCAST 2003. Lecture Notes in Computer Science, vol 2809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45210-2_29
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DOI: https://doi.org/10.1007/978-3-540-45210-2_29
Publisher Name: Springer, Berlin, Heidelberg
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