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<b:Sources SelectedStyle="" xmlns:b="http://schemas.openxmlformats.org/officeDocument/2006/bibliography"  xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" >
<b:Source>
<b:Tag>Dimosthenis Karatzas2008</b:Tag>
<b:SourceType>Proceedings</b:SourceType>
<b:Year>2008</b:Year>
<b:ConferenceName>19th International Conference on Pattern Recognition</b:ConferenceName>
<b:Author>
<b:Author><b:NameList>
<b:Person><b:Last>Dimosthenis Karatzas</b:Last></b:Person>
<b:Person><b:Last>Mar&#231;al Rusi&#241;ol</b:Last></b:Person>
<b:Person><b:Last>Coen Antens</b:Last></b:Person>
<b:Person><b:Last>Miquel Ferrer</b:Last></b:Person>
<b:Person><b:Last>ICPR</b:Last></b:Person>
</b:NameList></b:Author>
</b:Author>
<b:Title>Segmentation Robust to the Vignette Effect for Machine Vision Systems</b:Title>
<b:Comments>The vignette effect (radial fall-off) is commonly encountered in images obtained through certain image acquisition setups and can seriously hinder automatic analysis processes. In this paper we present a fast and efficient method for dealing with vignetting in the context of object segmentation in an existing industrial inspection setup. The vignette effect is modelled here as a circular, non-linear gradient. The method estimates the gradient parameters and employs them to perform segmentation. Segmentation results on a variety of images indicate that the presented method is able to successfully tackle the vignette effect.</b:Comments>
</b:Source>
</b:Sources>