Colour in Context
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Shadow Resistant Road Segmentation from a Mobile Monocular System

J.M. Alvarez, Antonio Lopez, Ramon Baldrich
Iberian Conference on Pattern Recognition and Image Analysis - 2007
Download the publication : ALB2007.pdf [1Mo]  
An essential functionality for advanced driver assistance systems (ADAS) is road segmentation, which directly supports ADAS applications like road departure warning and is an invaluable background segmentation stage for other functionalities as vehicle detection. Unfortunately, road segmentation is far from being trivial since the road is in an outdoor scenario imaged from a mobile platform. For instance, shadows are a relevant problem for segmentation. The usual approaches are ad hoc mechanisms, applied after an initial segmentation step, that try to recover road patches not included as segmented road for being in shadow. In this paper we argue that by using a different feature space to perform the segmentation we can minimize the problem of shadows from the very beginning. Rather than the usual segmentation in a color space we propose segmentation in a shadowless image which is computable in real–time using a color camera. The paper presents comparative results for both asphalted and non–asphalted roads, showing the benefits of the proposal in presence of shadows and vehicles.

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BibTex references

@InProceedings\{ALB2007,
  author       = "J.M. Alvarez and Antonio Lopez and Ramon Baldrich",
  title        = "Shadow Resistant Road Segmentation from a Mobile Monocular System",
  booktitle    = "Iberian Conference on Pattern Recognition and Image Analysis",
  year         = "2007",
  abstract     = "An essential functionality for advanced driver assistance systems
(ADAS) is road segmentation, which directly supports ADAS applications
like road departure warning and is an invaluable background
segmentation stage for other functionalities as vehicle detection. Unfortunately,
road segmentation is far from being trivial since the road is
in an outdoor scenario imaged from a mobile platform. For instance,
shadows are a relevant problem for segmentation. The usual approaches
are ad hoc mechanisms, applied after an initial segmentation step, that
try to recover road patches not included as segmented road for being in
shadow. In this paper we argue that by using a different feature space to
perform the segmentation we can minimize the problem of shadows from
the very beginning. Rather than the usual segmentation in a color space
we propose segmentation in a shadowless image which is computable in
real\–time using a color camera. The paper presents comparative results
for both asphalted and non\–asphalted roads, showing the benefits of the
proposal in presence of shadows and vehicles.",
  url          = "http://cat.uab.es/Public/Publications/2007/ALB2007"
}

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