Feature extraction of volume data based on multi-scale representation

Authors:
Y. Wu;E. C. Chang;Z. Huang;M. S. Kankanhalli
Affiliations:
National University of Singapore, Singapore;National University of Singapore, Singapore;National University of Singapore, Singapore;National University of Singapore, Singapore
Venue:
Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Year:
2003

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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.