A image-based quality inspection system for automated handling of wooden parts

In this paper, we present a system for real-time quality inspection of wooden parts. The quality inspection system was developed for classifying wooden parts in an application with automated robotic handling operations. An essential feature is the detection of different grain patterns from the part surface. The quality inspection consists of CMOS camera imaging, texture analysis of images, and feature-based classification for evaluating the surface quality. The features are extracted from blobs and the classification algorithm relies on support vector machines. Based on our test results, the reliability of the classification is at a sufficient level.