.png){kind=icon}
返回
Boundary simplification using a multiscale dominant-point detection algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/S0031-3203(97)00104-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we intend to characterize boundaries using the Scale-space theory. The aim we try to achieve is the description of a boundary in relation to a subset of points-dominant points-that are obtained From a new multiscale representation of the boundary. Dominant points are characterized by a high curvature value (in the original or smoothed boundary). As a result, the boundary is represented using those points as well as an appropriate interpolation method (the linear one in the simplest case) among them. As the basic tool of our work we will introduce a new multiscale dominant point detection algorithm that detects the points at their natural scales through a reliability condition with respect to the original curve. Because we want to apply the algorithms on complex enough boundaries, we use cartographic boundaries (in which several structures can be obtained at different scales) to evaluate the results. (C) 1998 Published by Elsevier Science Ltd on behalf of the Pattern Recognition Society. All rights reserved.
Keyword:
multiscale representation
line simplification
scale-space
dominant points
natural scale
interpolation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.6
论文数:
1.3W
被引数:
4.5W
机构
暂无机构信息
引用论文
Grape and wine sensory attributes correlate with pattern-based discrimination of Cabernet Sauvignon wines by a peptidic sensor array.png)
Tetrahedron
TetrahedronIF0
PREAI
分享收藏Self-focusing effects of dispositional self-consciousness, mirror presence, and audience presence.性格自我意识、镜像存在和观众存在的自我聚焦效应。
PREAI
分享收藏
查看更多内容