Color analysis of defects for automated visual inspection of pine wood

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Abstract
The goal of our research is to develop an automated system for the visual inspection of wood surfaces. Our present approach to inspection is based on the computing of color and texture features for non-overlapping image windows and classifying each window into one of a set of prototype defect classes on the basis of training statistics. The choice of features and final classification strategy nevertheless requires an analysis of the color properties of defects and clear wood. The spectra reflectance characteristics of objects in the visible spectrum were used in the color analysis, these being invariant properties of objects concerned. The analysis was performed for pine wood, employing measurements of the spectral reflectance characteristics of clear wood and visible defects. This enabled a few types of clear wood to be classified in terms of the degree of color homogeneity, defects recognizable against the background of the clear wood and defects differentiable by color. The results indicate that color provides very valuable information for the discrimination of wood defects. Such spectral reflectance characteristics of defects can also be used to formulate the requirements for a machine vision system.

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