Multiscale Laplacian operators for feature extraction on irregularly distributed 3-D range data

Authors:
Shanmugalingam Suganthan;Sonya Coleman;Bryan Scotney
Affiliations:
School of Computing and Intelligent Systems, University of Ulster, Northern Ireland;School of Computing and Intelligent Systems, University of Ulster, Northern Ireland;School of Computing and Information Engineering, University of Ulster, Northern Ireland
Venue:
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Year:
2008

Citing 5
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Abstract

Multiscale feature extraction in image data has been investigated for many years. More recently the problem of processing images containing irregularly distribution data has became prominent. We present a multiscale Laplacian approach that can be applied directly to irregularly distributed data and in particular we focus on irregularly distributed 3D range data. Our results illustrate that the approach works well over a range of irregular distributed and that the use of Laplacian operators on range data is much less susceptive to noise than the equivalent operators used on intensity data.