Cetiner I., Var A. A. , Cetiner H.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.393-396 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2014.6830248
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.393-396


In this study, quality of class of final product is intended to automatically determine by setting properly distribution and number of defects on wood. Nowadays number of defects and quality of wood is determined by their distribution. The most common type of defect is called knot by reducing the resistance of a wooden part. Selection and classification of wood manually is difficult, costly and time-consuming process. At this point automatic defect detection methods have been proposed to affect the quality of the final product and defects are accurately automatically identified and analyzed. To this end, quality determination has been made according to TS 11790 and EN 13990 standards on databases that are containing wood images.