• DocumentCode
    2799211
  • Title

    Content-based Image Retrieval using Multiple Shape Descriptors

  • Author

    Sarfraz, M. ; Ridha, A.

  • Author_Institution
    King Fahd Univ. of Pet. & Miner., Dhahran
  • fYear
    2007
  • fDate
    13-16 May 2007
  • Firstpage
    730
  • Lastpage
    737
  • Abstract
    In this paper we investigate content-based image retrieval using various shape descriptors. The descriptors include 11 moment invariants, area ratios (3-concentric ring based and 8-sector based) and simple shape descriptors (eccentricity, compactness, convexity, rectangularity, and solidity). The similarity measures used are Euclidean distance and Cosine correlation coefficient. For testing, 220 binary images from SQUID categorized into 12 image groups are used. Simple Shape Descriptors with Euclidean distance achieve the best average precision (0.593). Combining simple shape descriptors and area ratios, also using Euclidean distance as similarity measure, results in 3.29% improvement.
  • Keywords
    content-based retrieval; correlation methods; image retrieval; Euclidean distance; content-based image retrieval; cosine correlation coefficient; multiple shape descriptor; Computational efficiency; Computer science; Content based retrieval; Euclidean distance; Histograms; Image retrieval; Information retrieval; Minerals; Petroleum; Shape measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications, 2007. AICCSA '07. IEEE/ACS International Conference on
  • Conference_Location
    Amman
  • Print_ISBN
    1-4244-1030-4
  • Electronic_ISBN
    1-4244-1031-2
  • Type

    conf

  • DOI
    10.1109/AICCSA.2007.370714
  • Filename
    4231042