A Data Structure for Triangular Dissection of Multi-Resolution Images

A Data Structure for Triangular Dissection of Multi-Resolution Images
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多分辨率图像三角剖分的数据结构

DOI:
10.1109/snpd.2014.6888732
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发表时间:
2014
期刊:
Proc. 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014)
影响因子:
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通讯作者:
Takeo Yaku
Takeo Yaku
中科院分区:
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文献类型:
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作者:
Taiyou Kikuchi;Koichi Anada;Shinji Koka;Youzou Miyadera;Takeo Yaku

文献摘要

相似文献

在这项工作中,考虑了表示栅格数据的多分辨率图像的非均匀矩形剖分。具体地说,为了提供更有效的特征提取,将非均匀矩形剖分改为三角形剖分。我们提出了一种生成三角剖分的方法,该方法保持了“八元网格”的性质,并开发了一种适用于提取图像特征(脊线、山谷等)的列表结构。从地形图上。我们提出了一种称为“H12Code”的详细列表结构,并给出了使用H12Code列表进行特征提取的例子。
In this work, the heterogeneous rectangular dissections that represent multi-resolution images of raster data are considered. Specifically, heterogeneous rectangular dissections are changed to triangular dissections in order to provide more effective feature extraction. We propose a method of generating triangular dissections that maintains “octgrid” properties and have developed a list structure suitable for extracting image features (ridges, valleys, etc.) from terrain maps. We propose a detailed list structure called “H12Code” and present examples of feature extraction using H12Code lists.