A COLOR VISION APPROACH FOR GRADING LUMBER

Automated visual grading of lumber is attractive for the sawmill industry. The accuracy and the homogeneity of the quality grading in voluminous production easily improves the profit obtained from it.

In this paper we describe a color vision based approach to automated grading of dried softwood lumber. The proposed inspection principle is to recognize the sound wood regions early as this reduces the computational requirements at later stages. This is important because color increases the data volumes significantly over grey scale images. The computational solutions have turned out to be simpler than with gray scale data, compensating for the higher cost of the imaging system.