Please use this identifier to cite or link to this item: https://doi.org/10.1145/604471.604506
Title: Feature extraction of volume data based on multi-scale representation
Authors: Wu, Y.
Chang, E.C. 
Huang, Z. 
Kankanhalli, M.S. 
Keywords: Applications
Feature detection
Medical imaging
Multi-scale
Scale-space
Scientific visualization
Volume processing
Issue Date: 2003
Source: Wu, Y.,Chang, E.C.,Huang, Z.,Kankanhalli, M.S. (2003). Feature extraction of volume data based on multi-scale representation. Proceedings of the 1st International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia, GRAPHITE '03 : 175-180. ScholarBank@NUS Repository. https://doi.org/10.1145/604471.604506
Abstract: In this paper, we present a novel algorithm that can detect and extract salient points as features in 3-D volume datasets. This algorithm extracts not only the locations of feature points, but also finds out the scales at which the features are most significant. It applies the scale-space theory by adaptively processing the input volume in a few discrete scales. The features points, as well as their scales, detected can be used for subsequent processing, such as content-based volume data authentication and content-based volume rendering.We have implemented the algorithm and tested its effectiveness on several volume datasets. Some optimization has also been done on time-consuming intermediate steps to speed up the feature detection process. Copyright © 2003 by the Association for Computing Machinery, Inc.
Source Title: Proceedings of the 1st International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia, GRAPHITE '03
URI: http://scholarbank.nus.edu.sg/handle/10635/41014
ISBN: 1581135785
DOI: 10.1145/604471.604506
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