Accurate matching of two-dimensional shapes using the minimal tolerance zone error

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Automated visual geometric inspection of machined parts depends upon the ability to determine the underlying parameters of a shape model that will best fit the reference shape to the real shape captured. This paper presents a parametric approach for the matching of two-dimensional profiles, which are composed of straight-line segments and circular arcs, based on the tolerancing requirements defined by the AINSI standards. The shape matching problem is formulated as a minimax optimization model and a procedure for solving this optimization model is developed. Experimental results have shown the proposed algorithm to be consistently accurate and extremely fast.

Original languageEnglish (US)
Pages (from-to)889-899
Number of pages11
JournalImage and Vision Computing
Volume15
Issue number12
StatePublished - Jan 1 1997

Fingerprint

Inspection

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Vision and Pattern Recognition

Cite this

@article{cff321df9f71417e89d6c7a614ade055,
title = "Accurate matching of two-dimensional shapes using the minimal tolerance zone error",
abstract = "Automated visual geometric inspection of machined parts depends upon the ability to determine the underlying parameters of a shape model that will best fit the reference shape to the real shape captured. This paper presents a parametric approach for the matching of two-dimensional profiles, which are composed of straight-line segments and circular arcs, based on the tolerancing requirements defined by the AINSI standards. The shape matching problem is formulated as a minimax optimization model and a procedure for solving this optimization model is developed. Experimental results have shown the proposed algorithm to be consistently accurate and extremely fast.",
author = "Ventura, {Jose Antonio} and Wenhua Wan",
year = "1997",
month = "1",
day = "1",
language = "English (US)",
volume = "15",
pages = "889--899",
journal = "Image and Vision Computing",
issn = "0262-8856",
publisher = "Elsevier Limited",
number = "12",

}

Accurate matching of two-dimensional shapes using the minimal tolerance zone error. / Ventura, Jose Antonio; Wan, Wenhua.

In: Image and Vision Computing, Vol. 15, No. 12, 01.01.1997, p. 889-899.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Accurate matching of two-dimensional shapes using the minimal tolerance zone error

AU - Ventura, Jose Antonio

AU - Wan, Wenhua

PY - 1997/1/1

Y1 - 1997/1/1

N2 - Automated visual geometric inspection of machined parts depends upon the ability to determine the underlying parameters of a shape model that will best fit the reference shape to the real shape captured. This paper presents a parametric approach for the matching of two-dimensional profiles, which are composed of straight-line segments and circular arcs, based on the tolerancing requirements defined by the AINSI standards. The shape matching problem is formulated as a minimax optimization model and a procedure for solving this optimization model is developed. Experimental results have shown the proposed algorithm to be consistently accurate and extremely fast.

AB - Automated visual geometric inspection of machined parts depends upon the ability to determine the underlying parameters of a shape model that will best fit the reference shape to the real shape captured. This paper presents a parametric approach for the matching of two-dimensional profiles, which are composed of straight-line segments and circular arcs, based on the tolerancing requirements defined by the AINSI standards. The shape matching problem is formulated as a minimax optimization model and a procedure for solving this optimization model is developed. Experimental results have shown the proposed algorithm to be consistently accurate and extremely fast.

UR - http://www.scopus.com/inward/record.url?scp=0031371930&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031371930&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0031371930

VL - 15

SP - 889

EP - 899

JO - Image and Vision Computing

JF - Image and Vision Computing

SN - 0262-8856

IS - 12

ER -