Automated quality classification of wooden parts for flexible manufacturing

Jukka Koskinen (Corresponding Author), Tapio Vaarala, Juha Alatalo, Tapio Heikkilä

    Research output: Contribution to journalArticleScientificpeer-review


    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.
    Original languageEnglish
    Pages (from-to)239-243
    JournalGSTF Journal of Engineering Technology (JET)
    Issue number1
    Publication statusPublished - 2013
    MoE publication typeA1 Journal article-refereed


    • wood industry
    • support vector machines
    • image analysis


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