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

    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.
    Original languageEnglish
    Pages (from-to)239-243
    Number of pages5
    JournalGSTF Journal of Engineering Technology (JET)
    Volume2
    Issue number1
    DOIs
    Publication statusPublished - 2013
    MoE publication typeNot Eligible

    Keywords

    • wood industry
    • support vector machines
    • image analysis

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