Abstract
In the lumber and wood processing industry, most visual quality inspections are still done by trained human operators. Visual inspection is a tedious and repetitive task that involves a high likelihood of human error. Currently, new automated solutions with high-resolution cameras and visual inspection algorithms are being tested, but they are not always fast and accurate enough for real-time industrial applications. This paper proposes an automatic visual inspection system for the location and classification of defects on the wood surface. We adopted a faster region-based convolutional neural network (faster R-CNN) for the identification of defects on wood veneer surfaces. Faster R-CNN has been successfully used in medical image processing and object tracking before, but it has not yet been applied for wood panel surface quality assurance. To improve the results, we used pre-trained AlexNet, VGG16, BNInception, and ResNet152 neural network models for transfer learning. The results of the experiments using a synthetically augmented dataset are presented. The best average accuracy of 80.6% was obtained using the pretrained ResNet152 neural network model. By combining all the defect classes, a 96.1% accuracy of finding wood panel surface defects was achieved.
Highlights
According to the United Nations, there is a growth in the wood industry worldwide
We have described the development of an automatic visual inspection system for the location and classification of defects on wood veneer surfaces
The results demonstrated the applicability of data augmentation and transfer learning techniques for the identification of four classes of wood veneer surface defects
Summary
According to the United Nations, there is a growth in the wood industry worldwide. In 2017, the world production of wood panels reached 402 million m3 per year [1]. In the Asian market alone, timber production grew by 40% over the period 2011–2015. One of the largest wood processing areas is the production of wood veneer, which, together with the production of plywood panels, has become the dominant market, accounting for 39% of the total wood processing market. Wood veneer is used for coating and decorating surfaces of furniture, doors, or interior design elements. Due to the heterogeneity of the raw material and the complexity of the manufacturing process, the panels produced may have various defects, such as scratches, stains, or wood cores.
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