Automated Quality Classification of Wooden Parts for Flexible Manufacturing

Jukka Koskinen, Tapio Vaarala, Juha Alatalo, Tapio Heikkilä

Abstract


In this paper we present a system for real-time quality
inspection of wooden parts. The quality inspection system is
based on computer vision and was developed for classifying
wooden parts in an application with automated robotic handling
operations. The quality inspection stands for evaluation of the
surface quality, including image capture, and feature-based
surface classification. 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.


Keywords


Wood industry, Support vector machines, Image analysis

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