An optimum feature extraction method for texture classification

Avci E., Sengur A., Hanbay D.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.36, sa.3, ss.6036-6043, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.eswa.2008.06.076
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.6036-6043
  • Anahtar Kelimeler: Pattern recognition, Texture classification, Optimum feature extraction, Discrete wavelet transform, Entropy, Energy, Genetic algorithm, Neural networks, Intelligent systems, SELECTION
  • İnönü Üniversitesi Adresli: Hayır

Özet

Texture can be defined as a local statistical pattern of texture primitives in observer's domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. In this paper a novel method, which is an intelligent system for texture classification is introduced. It used a combination of genetic algorithm, discrete wavelet transform and neural network for optimum feature extraction from texture images. An algorithm called the intelligent system, which processes the pattern recognition approximation, is developed. We tested the proposed method with several texture images. The overall success rate is about 95%. (C) 2008 Published by Elsevier Ltd.