Abstract
With the development of wood industry, the processing of wood products become more significant. This paper discusses the development of machine vision system used to inspect and classify the various types of defects of wood surface. The surface defects means the variations of colour and texture. The machine vision system is to detect undesirable “defects” that can appear on the surface of rough wood lumber. A neural network was used within the Blackboard framework for a labeling verification step of the high-level recognition module of vision system. The system has been successfully tested on a number of boards from several different species.
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References
Kovivo, A. J. and C. W. Kim. 1986. Classification of surface defects on wood boards. IEEE Inter. Conf. on System, Man, and Cybernetics.pp. 1431–1436.
Fukunaga, K. 1989. Introduction to Statistical Pattern Recognition. Academic Press, N.Y.
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Funded by Found of the National Natural Science Foundation of China
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Keqi, W., Jingfeng, B. A machine vision system for inspecting wood surface defects by using neural network. J. Northeast For. Univ. 7, 63–65 (1996). https://doi.org/10.1007/BF02843098
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DOI: https://doi.org/10.1007/BF02843098