An efficient rotation invariant feature extraction method based on ring projection technique Çember izdüsüm teknigine dayali döndürmeden bagimsiz etkili bir öznitelik çikarim yöntemi

Atas M., Kaya Y., Uyar M.

2013 21st Signal Processing and Communications Applications Conference, SIU 2013, Haspolat, Türkiye, 24 - 26 Nisan 2013 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2013.6531229
  • Basıldığı Şehir: Haspolat
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Local binary pattern, Pattern recognition, Rotation-invariant ring projection, Texture classification
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

This study presents an efficient rotation-invariant feature extraction method based on ring projection technique. The main advantage of this method is to reduce the number of sampling frequency of standard ring projection method. The proposed method is compared with the ring projection and local binary patterns according to the computational speed of the feature extraction and classification accuracy. By incrementally rotating first image of each texture class by 30 and 45 degrees enrich the dataset and yield two texture datasets having totally 1332 and 888 samples from the original Brodatz texture image dataset, respectively. Throughout the study Weka machine learning and data mining tool is utilized. As a classifier Naive Bayes, Bagging and J48 decision tree are used due to their simplicity and speed. Classification performance is evaluated via 10 fold cross validation technique. It is observed that, the proposed method outperforms other alternatives in terms of classification accuracy and feature extraction speed. © 2013 IEEE.