Efficient measurement procedures for compound part profile by computer vision

C. Alec Chang, Liang-Hsuan Chen, Jiunn Ing Ker

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

It is apparent that automated inspection for manufacturing is on the threshold of broad industrial utilization. One key problem in manufacturing applications of automated inspection is how to find fast and efficient methods using economical computers that industry can afford. Moreover, most mechanical designers set only overall tolerances for part geometric features. In computer vision inspection, as well as in the use of other automated inspection devices and coordinate measuring machines (CMM) the errors of representing each geometric features should be identified separately. The proposed statistical inference method provides a scientific basis for setting inspection tolerances in original geometric space which are compatible with engineering specifications. The results of this presentation should supply industrial practitioners with an accurate and fast approach for on-line part profile inspection.

Original languageEnglish
Pages (from-to)375-377
Number of pages3
JournalComputers and Industrial Engineering
Volume21
Issue number1-4
DOIs
Publication statusPublished - 1991 Jan 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

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