CLASSIFICATION of KNOT DEFECT TYPES


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

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Türkiye, 23 - 25 Nisan 2014, ss.1086-1089 identifier identifier

  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2014.6830422
  • Basıldığı Şehir: Trabzon
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1086-1089

Özet

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%.