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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Boundary simplification using a multiscale dominant-point detection algorithm
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Boundary simplification using a multiscale dominant-point detection algorithm

机译:使用多尺度优势点检测算法的边界简化

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摘要

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 oi 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. [References: 31]
机译:在本文中,我们打算使用比例空间理论来描述边界。我们试图实现的目标是描述与点的子集(主要点)相关的边界,这些子集是从边界的新多尺度表示中获得的。优势点的特征在于高曲率值(在原始边界或平滑边界中)。结果,使用这些点以及其中的适当插值方法(在最简单的情况下为线性方法)来表示边界。作为我们工作的基本工具,我们将引入一种新的多尺度优势点检测算法,该算法通过相对于原始曲线的可靠性条件以自然尺度检测这些点。因为我们想在足够复杂的边界上应用算法,所以我们使用制图边界(可以在不同比例下获得多个结构)来评估结果。 (C)1998由Elsevier Science Ltd代表模式识别协会出版。版权所有。 [参考:31]

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