AUTOMATIC DETECTION OF DEFECTS ON BIRCH WOOD BOARDS

In a factory which produces veneer boards from birch wood, grading of the boards into different quality categories is usually part of the pr oduction process. To improve the efficiency of grading, attempts are b eing made to automate it using automated visual inspection (AVI). Inte gral to the process of inspection is segmentation. Segmentation is the part of the AVI process concerned with separating clear wood and defe ctive areas in the image. This paper describes a system that is used t o segment the images of birch wood boards. The system consists of four modules which are called global adaptive thresholding, multi-level th resholding, row-by-row adaptive thresholding and vertical profiling. T he paper gives details of the four modules and presents the results ob tained in segmenting images of a large sample of birch wood boards.