The k-nearest neighbor method for automatic identification of wood products

The complete follow-up of a product from its origin to its final use has been strongly developed in recent years. In wood industries, the implementation of ordinary identification systems presents implantation problems, mainly because of the extremely variable nature of the material and the particular features of the manufacturing process. In order to allow follow-up of products, new solutions have been considered by the use of non-destructive control techniques. We implemented an identification system, where each product is considered as unique with unique features. We use a microwave sensor to obtain an intrinsic signal of a wood piece and then perform its identification. The objective is to determine a process for identifying signals. The algorithm developed for pattern identification is based on the k-nearest neighbor method. To increase the performance of this algorithm, the signals are pretreated. Signals already recorded in the database are positioned in the space to n-dimensions. When a product is to be identified, it also sees its signal positioned; the signal having a distance criterion nearest the reference is located. The identifying algorithm developed shows an error of 1.5%.