Classification of KNOT defect types Budak kusur tiplerinin siniflandirilmasi
2014 22nd Signal Processing and Communications Applications Conference, SIU 2014, Trabzon, Turkey, 23 - 25 April 2014, pp.1086-1089, (Full Text)
- Publication Type: Conference Paper / Full Text
- Doi Number: 10.1109/siu.2014.6830422
- City: Trabzon
- Country: Turkey
- Page Numbers: pp.1086-1089
- Keywords: Approximation Coefficients, KNN Classification, Knot types, Wavelet Moment
- Isparta University of Applied Sciences Affiliated: Yes
Abstract
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%. © 2014 IEEE.