Artificial Intelligence for a Structured-Light Imaging System

T.J. Gale (Australia)


Defect, Imaging, Neural network


This paper describes the application of artificial intelligence to a structured-light imaging system. Three approaches were considered involving classical logic, fuzzy logic and an artificial neural network (ANN). Images were taken of both faulty and non-faulty confectionery product and the effectiveness of each approach in identifying reject product was determined. It was found that the effectiveness of all three approaches was greater than 90%, with the ANN being superior. It was proposed that the ANN system be further developed to increase the capabilities of this system.

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