Openly accessible

Machine vision system for automatic inspection of surface defects in aluminum die casting

Frayman, Yakov, Zheng, Hong and Nahavandi, Saeid 2006, Machine vision system for automatic inspection of surface defects in aluminum die casting, Journal of advanced computational intelligence and intelligent informatics, vol. 10, no. 3, pp. 281-286, doi: 10.20965/jaciii.2006.p0281.

Attached Files
Name Description MIMEType Size Downloads

Title Machine vision system for automatic inspection of surface defects in aluminum die casting
Author(s) Frayman, Yakov
Zheng, Hong
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Journal name Journal of advanced computational intelligence and intelligent informatics
Volume number 10
Issue number 3
Start page 281
End page 286
Publisher Fuji Technology Press Ltd
Place of publication Tokyo, Japan
Publication date 2006
ISSN 1343-0130
Keyword(s) aluminum die casting
automatic vision inspection
genetic algorithms
surface defect recognition
Language eng
DOI 10.20965/jaciii.2006.p0281
Indigenous content off
Field of Research 080104 Computer Vision
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30004038

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 10 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 1778 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Mon, 07 Jul 2008, 09:10:19 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.