• DocumentCode
    3111288
  • Title

    Efficient image retrieval based on texture features

  • Author

    Fazal-e-Malik ; Baharudin, Baharum

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. Teknol. PETRONAS, Tronoh, Malaysia
  • fYear
    2011
  • fDate
    19-20 Sept. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A quick and accurate algorithm for content-based image retrieval (CBIR) is proposed in this paper. The retrieval of the similar images using proposed algorithm from the database is based on the statistical texture features. The basic idea is to convert the RGB color image into grayscale image to reduce the computation speed and increase efficiency. The grayscale image is divided into blocks of different sizes. The statistical texture features are extracted by using the probability distribution of intensity levels in all blocks. In the experiment, the efficiency of feature extraction and accuracy of the image retrieval are measured for different block size methods using the proposed algorithm. The Corel database was used for testing. As a result the proposed CBIR algorithm provided higher performance in terms of efficiency and accuracy.
  • Keywords
    content-based retrieval; feature extraction; image colour analysis; image retrieval; image texture; CBIR algorithm; Corel database; RGB color image; computation speed; content-based image retrieval; grayscale image; intensity level; probability distribution; statistical texture feature extraction; Databases; Entropy; Feature extraction; Gray-scale; Image color analysis; Probability distribution; Vectors; content-based image retrieval (CBIR); intensity levels; statistical texture features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    National Postgraduate Conference (NPC), 2011
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4577-1882-3
  • Type

    conf

  • DOI
    10.1109/NatPC.2011.6136308
  • Filename
    6136308