Clustering-based volume segmentation design

被引：0

作者：

Xu Q. ^{[1
]}

Zhao Z. ^{[1
]}

Wang W. ^{[1
]}

机构：

[1] Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province

来源：

International Journal of Advanced Media and Communication | 2016年 / 6卷 / 2-4期

关键词：

Clustering; Data structure; Interesting data segment; Segmentation; Volumetric;

D O I：

10.1504/IJAMC.2016.080962

中图分类号：

学科分类号：

摘要：

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. Copyright © 2016 Inderscience Enterprises Ltd.

引用

页码：156 / 166

页数：10

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