A skeletonization algorithm using chamfer distance transformation adapted to rectangular grids

Many skeletonization methods based on distance transformation have been proposed. They are generally designed for square grids. However most industrial vision systems digitize images on rectangular grids. These images are then resampled to obtain square pixels. In this paper we propose a skeletoniza...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 2; pp. 131 - 135 vol.2
Main Authors Chehadeh, Y., Coquin, D., Bolon, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Euclidean distance
Grid computing
Image analysis
Image reconstruction
Iterative methods
Machine vision
Pattern recognition
Pixel
Skeleton
Topology
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ISBN9780818672828
081867282X
ISSN1051-4651
DOI10.1109/ICPR.1996.546738

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Summary:Many skeletonization methods based on distance transformation have been proposed. They are generally designed for square grids. However most industrial vision systems digitize images on rectangular grids. These images are then resampled to obtain square pixels. In this paper we propose a skeletonization algorithm directly adapted to rectangular grids. We use the efficient skeletonization method of Arcelli and Sanniti di Baja (1993), based on the Euclidean distance transform, and we adapt it to chamfer distances computed on rectangular grids. We propose some modifications to this algorithm. Some results are given and discussed.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.546738