Automated visual inspection of birch wood boards

To improve upon the accuracy of human graders in the grading of birch wood boards, an automated visual inspection framework has been proposed. The framework includes a modular segmentation system, artificial intelligence-based post-processing of the segmented image, neural-network-based feature extraction and synergistic classification. Overall, it can be seen that the achieved results are significantly better than those achievable by human inspectors.