Authors: Qian Xu; Zhengxu Zhao; Wei Wang
Addresses: Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province, 050043, China ' Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province, 050043, China ' Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province, 050043, China
Abstract: A novel volumetric data clustering work introduced in this paper aim to cluster the volume data and filter out its inherent noise via extracting the data structure and indicating the useless segments. On the basis of classic segmentation algorithms, this research focuses on exploring volume-based segmentation solutions and property-oriented display mechanisms to assist with the decision-making stage involved in associated volume data manipulation works. As the resulting outputs of this design, the occlusion relationships embedded into volumetric space can be precisely oriented in the manner of visualised partition feature(s). This data visualisation process can be accomplished automatically based on the classified information. In addition, a novel manipulation operation can be built via extracting wireframe-based surfaces from the segmentation results.
Keywords: volumetric data clustering; data structure; interesting data segments; volume segmentation design; occlusion relationships; data visualisation.
International Journal of Advanced Media and Communication, 2016 Vol.6 No.2/3/4, pp.156 - 166
Received: 25 Nov 2015
Accepted: 08 Feb 2016
Published online: 10 Dec 2016 *