Machine vision system for automatic inspection of surface defects in aluminum die casting
Data(s) |
01/01/2006
|
---|---|
Resumo |
A camera based machine vision system for the automatic inspection of surface defects in aluminum die casting is presented. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Fuji Technology Press Ltd |
Relação |
http://dro.deakin.edu.au/eserv/DU:30004038/frayman-machinevision-2006.pdf http://www.fujipress.jp/finder/xslt.php?mode=present&inputfile=JACII001000030005.xml |
Palavras-Chave | #aluminum die casting #automatic vision inspection #genetic algorithms #surface defect recognition |
Tipo |
Journal Article |