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Supervised Segmentation of Textures in Backscatter Images
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104834516th International Conference on Patt ...
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Pavel Paclík, Delft University of Technology
Robert P. W. Duin, Delft University of Technology
Geert M. P. van Kempen, Unilever R&D Vlaardingen
Reinhard Kohlus, Unilever R&D Vlaardingen
In this paper we present an application of statistical pattern recognition for segmentation of backscatter images (BSE) in product analysis of laundry detergents. Currently, application experts segment BSE images interactively which is both time consuming and expert dependent. We present a new, automatic, procedure for supervised BSE segmentation which is trained using additional multi-spectral EDX images. Each time a new feature selection procedure is employed to find a convenient feature subset for a particular segmentation problem. The performance of the presented algorithm is evaluated using ground-truth segmentation results. It is compared with that of interactive segmentation performed by the analyst.
Citation:
Pavel Paclík, Robert P. W. Duin, Geert M. P. van Kempen, Reinhard Kohlus, "Supervised Segmentation of Textures in Backscatter Images," icpr, vol. 2, pp.20490, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002
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