Résumé: We introduce a novel method for identi .cation of objects of interest in volume data. Our approach conveys the information contained in two essentially different concepts, the object ’s boundaries and the narrow solid structures, in an easy and uniform way. The second- order derivative operators in directions reachingminimal response are employed for this task. To show the superior performance of our method, we provide a comparison with its main competitor F extraction from areas of maximal gradient magnitude. We show that our approach provides the possibility to represent volume data by a subset of a nominal size. Practical applications of our method include fast volume display due to object- space oriented techniques, progressive visualization over the network and the related generation of preview data sets for web- based repositories. For these applications, the size of the representative subset can be estimated automatically with respect to the bottleneck of the visualization system or network bandwidth.

Langue: Anglais