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

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.1086-1089 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2014.6830422
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.1086-1089
  • Süleyman Demirel University Affiliated: Yes


In this study, the experimental studies were carried out on a database containing the types of wood knot. After preprocessing on the images in the database, specific features to knot were obtained using wavelet moments feature extraction algorithm. Type description is carried out with KNN classification algorithm by selecting most distinguishing the approximation coefficients on these features. In conclusion, knot images could be classified with the success rate of 98%.