Efficient measurement procedures for compound part profile by computer vision

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

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)375-377
頁數3
期刊Computers and Industrial Engineering
21
發行號1-4
DOIs
出版狀態Published - 1991 一月 1

All Science Journal Classification (ASJC) codes

  • 電腦科學(全部)
  • 工程 (全部)

指紋

深入研究「Efficient measurement procedures for compound part profile by computer vision」主題。共同形成了獨特的指紋。

引用此