Recognition of Similar Wooden Surfaces with a Hierarchical Neural Network Structure

Abstract—The surface quality assurance check is an important task in industrial production of wooden parts. There are many automated systems applying different methods for preprocessing and recognition/classification of surface textures, but in the most cases these methods cannot produce very high recognition accuracy. This paper aims to propose a method for effective recognition of similar wooden surfaces applying simple preprocessing, recognition and classification stage. The method is based on simultaneously training two different neural networks with surface image histograms and their second derivatives. The combined outputs of these networks give an input training set for a third neural network to make the final decision. The proposed method is tested with image samples of seven similar wooden texture images and shows high recognition accuracy. The results are analyzed, discussed and further research tasks are proposed. Keywords—recognition; preprocessing; neural network; wooden surface I