DocumentCode
2405240
Title
Fuzzy machine vision based porosity detection
Author
Mehran, Pejman ; Demirli, Kudret ; Bone, Gary ; Surgenor, Brian
Author_Institution
Dept. of Mech. & Ind. Eng., Concordia Univ., Montreal, QC, Canada
fYear
2009
fDate
14-17 June 2009
Firstpage
1
Lastpage
6
Abstract
In this paper an objective fuzzy approach for fast and accurate porosity vision based inspection is presented. An automated methodology of detection of pores, which are formed in aluminum alloys during production of water-pumps for car engines with the die casting method, is described. The proposed method is based on the correlation of the core of pore candidates with twelve developed matrices resulted in five novel features. The fuzzy decision making on porosity detection adopted and presented in this paper, adds great value to the whole production system, by increasing the confidence of the inspectors in the machine performing real-time verification. The fuzzy porosity detection was carried out on a database of 105 gray level images. The proposed model properly identifies 93.36% of the pores in the entire database.
Keywords
automotive components; computer vision; die casting; fuzzy set theory; porosity; aluminum alloys; die casting method; fuzzy decision making; fuzzy machine vision; porosity detection; water-pumps; Aluminum alloys; Decision making; Die casting; Engines; Fuzzy systems; Image databases; Inspection; Machine vision; Production systems; Real time systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2009. NAFIPS 2009. Annual Meeting of the North American
Conference_Location
Cincinnati, OH
Print_ISBN
978-1-4244-4575-2
Electronic_ISBN
978-1-4244-4577-6
Type
conf
DOI
10.1109/NAFIPS.2009.5156423
Filename
5156423
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