Using AdaBoost classifiers in a hierarchical framework for classifying surface images of marble slabs

DOĞAN H., AKAY O.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.37, sa.12, ss.8814-8821, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 12
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1016/j.eswa.2010.06.019
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.8814-8821
  • Anahtar Kelimeler: Classification of marble slab images, Hierarchical classification, AdaBoost classification algorithms, CLASSIFICATION
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this paper, a new hierarchical classification method based on the use of various types of AdaBoost classification algorithms is proposed for automatic classification of marble slab images according to their quality. At first, features are extracted using the sum and difference histograms method and, at the second stage, different versions of the AdaBoost algorithms are used as classifiers together with those extracted features in a proposed hierarchical fashion. Performance of the proposed method is compared against performances of different types of neural network classifiers and a support vector machine (SVM) classifier. Computational results show that the proposed hierarchical structure employing AdaBoost algorithms performs superior to neural networks and the SVM classifier for classifying marble slab images in our large and diversified data set. (C) 2010 Elsevier Ltd. All rights reserved.