Defect Inspection of Wood Surfaces, Bogaziçi University Research Report, FBE-IE-08/97-12, 1997

ABSTRACT: In this paper the problem of using machine vision in automated quality inspection of wood surfaces is considered. Various techniques are studied for extracting features from wood surfaces that model the underlying texture. The results are then fed into several statistical and neural classification schemes that try to learn the defective and nondefective surfaces. The results are illustrated on real wood images, and the comparative results of the study are reported. The results indicate that automation of the inspection process is feasible in the production line.

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