Vision-based shape recognition and analysis of machined parts

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Machine vision has the potential to significantly impact both quality and productivity in computer integrated manufacturing, due to its versatility, flexibility and relative speed. Unfortunately, algorithmic development has not kept pace with advances in vision hardware technology, particularly in the areas of inspection and decision making. This paper deals with the development of machine vision algorithms for automated inspection of production parts. The inspection system presented in this work consists of three parts in series: segmentation, recognition and analysis. The input of this system is a set of ordered boundary data extracted from the object, and the output includes the identity of this object, and its pose, dimension and out-of-profile error, Computer experiments have shown the proposed algorithms to be consistently accurate and extremely fast. These algorithms can be easily programmable lo inspect different types of shapes, which makes the vision system generic and flexible. Furthermore, these algorithms were developed based on the current definitions of dimensioning and tolerancing standards provided by ANSI YI4-5M-I982, so that the results generated by the system are unique and interpretable.

Original languageEnglish (US)
Pages (from-to)101-135
Number of pages35
JournalInternational Journal of Production Research
Volume33
Issue number1
DOIs
StatePublished - Jan 1 1995

Fingerprint

Inspection
Computer vision
Computer integrated manufacturing
Productivity
Decision making
Hardware
Experiments
Machine vision
Segmentation
Computer experiments

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

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title = "Vision-based shape recognition and analysis of machined parts",
abstract = "Machine vision has the potential to significantly impact both quality and productivity in computer integrated manufacturing, due to its versatility, flexibility and relative speed. Unfortunately, algorithmic development has not kept pace with advances in vision hardware technology, particularly in the areas of inspection and decision making. This paper deals with the development of machine vision algorithms for automated inspection of production parts. The inspection system presented in this work consists of three parts in series: segmentation, recognition and analysis. The input of this system is a set of ordered boundary data extracted from the object, and the output includes the identity of this object, and its pose, dimension and out-of-profile error, Computer experiments have shown the proposed algorithms to be consistently accurate and extremely fast. These algorithms can be easily programmable lo inspect different types of shapes, which makes the vision system generic and flexible. Furthermore, these algorithms were developed based on the current definitions of dimensioning and tolerancing standards provided by ANSI YI4-5M-I982, so that the results generated by the system are unique and interpretable.",
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Vision-based shape recognition and analysis of machined parts. / Chen, J. M.; Ventura, Jose Antonio.

In: International Journal of Production Research, Vol. 33, No. 1, 01.01.1995, p. 101-135.

Research output: Contribution to journalArticle

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