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Multiscale Laplacian Operators for Feature Extraction on Irregularly Distributed 3-D Range Data

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Suganthan, S, Coleman, SA and Scotney, BW (2008) Multiscale Laplacian Operators for Feature Extraction on Irregularly Distributed 3-D Range Data. In: 6th International Conference on Computer Vision Systems, Vision for Cognitive Systems (ICVS 2008), Santorini, Greece. UNSPECIFIED. 10 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1007/978-3-540-79547-6_39

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.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:6850
Deposited By:Professor Bryan Scotney
Deposited On:20 Jan 2010 15:40
Last Modified:15 Jun 2011 11:07

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