An automatic optical sensor for vessels and fibbers quality inspection in pulp production

Abstract

Wood quality assessment is an important issue in the pulp and paper industry. In this paper an automatic visual inspection system for wood structural quality measurement is described. To improve statistical image segmentation a new logarithm based global contrast enhancement technique is described. Region identification and reconstruction is performed based on local morphological operators with constrained merge operations. A measurement technique, build-up upon a constrained optimisation problem, is described for fibber wall width computation. The method proves computational efficiency. The described inspection system uses only two control parameters.