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Refereed Papers

Segmentation Robust to the Vignette Effect for Machine Vision Systems

D. Karatzas, M. Rusinol, A. Jacobus, M. Ferrer

Proceedings of the 19th International Conference on Pattern Recognition, IEEE Computer Society, Tampa, USA, 2008

Abstract

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.

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