Automated quality classification of wooden parts for flexible manufacturing

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

Research output: Contribution to journalArticleProfessional

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 typeD1 Article in a trade journal

Keywords

  • wood industry
  • support vector machines
  • image analysis

Fingerprint Dive into the research topics of 'Automated quality classification of wooden parts for flexible manufacturing'. Together they form a unique fingerprint.

  • Cite this