SASI: a generic texture descriptor for image retrieval


Creative Commons License

Carkacioglu A., Yarman-Vural F.

PATTERN RECOGNITION, cilt.36, sa.11, ss.2615-2633, 2003 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 11
  • Basım Tarihi: 2003
  • Doi Numarası: 10.1016/s0031-3203(03)00171-7
  • Dergi Adı: PATTERN RECOGNITION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2615-2633
  • Anahtar Kelimeler: texture similarity, image retrieval, clique, autocorrelation, descriptor, CLASSIFICATION, SEGMENTATION, FEATURES
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

In this paper, a generic texture descriptor, namely, Statistical Analysis of Structural Information (SASI) is introduced as a representation of texture. SASI is based on statistics of clique autocorrelation coefficients, calculated over structuring windows. SASI defines a set of clique windows to extract and measure various structural properties of texture by using a spatial multi-resolution method. Experimental results, performed on various image databases, indicate that SASI is more successful then the Gabor Filter descriptors in capturing small granularities and discontinuities such as sharp corners and abrupt changes. Due to the flexibility in designing the clique windows, SASI reaches higher average retrieval rates compared to Gabor Filter descriptors. However, the price of this performance is increased computational complexity. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.