Combining MPEG-7 based visual experts for reaching semantics

Soysal M., Alatan A.

VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS, cilt.2849, ss.66-75, 2003 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2849
  • Basım Tarihi: 2003
  • Dergi Adı: VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.66-75
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Semantic classification of images using low-level features is a challenging problem. Combining experts with different classifier structures, trained by MPEG-7 low-level color and texture descriptors is examined as a solution alternative. For combining different classifiers and features, two advanced decision mechanisms are proposed, one of which enjoys a significant classification performance improvement. Simulations are conducted on 8 different visual semantic classes, resulting in accuracy improvements between 3.5-6.5%, when they are compared with the best performance of single classifier systems.