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

conference contribution
posted on 2004-01-01, 00:00 authored by Yakov Frayman, H Zheng, Saeid Nahavandi
A machine vision system is presented for the automatic inspection of surface defects in aluminium die casting. 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.


Title of proceedings

InTech'04 : Proceedings of the 5th International Conference on Intelligent Technologies


International Conference on Intelligent Technologies (5th : 2004 : Houston, Texas)


1 - 5


University of Houston-Downtown


Houston, Texas

Place of publication

Houston, Tex.

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End date




Publication classification

E1 Full written paper - refereed; E Conference publication

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Reproduced with the specific permission of the copyright owner.


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