期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：12
页码：117-126
出版社：SERSC
摘要：With the fast advances of sensing technologies in the past decade, a significant amount of discrete point data has been obtained. Some of these points are of poor quality because of measurement uncertainty at the geometric discontinuity of mechanical parts. In this paper, a particle swarm algorithm is developed for optimally-constrained multiple-line fitting of discrete data points. It contains two important technical components: a) constrained least-squares fitting of multiple lines, b) particle swarm search for optimal corner/edge points. The algorithm is applied to two-dimensional and three-dimensional cases. Numerical experiments indicate the effectiveness and high accuracy of the proposed approach, compared to the conventional method. It can be used for the accurate determination of sharp edges or corners based on discrete data points measured in high-precision inspection and manufacturing.
关键词：geometric discontinuity; particle swarm algorithm; sharp feature ;extraction; discrete data point
