• DocumentCode
    3301972
  • Title

    High-performance content-based image retrieval using DFS strategy

  • Author

    Ja-Hwung Su ; Chung-Chieh Hsu ; Ying, Josh Jia-Ching

  • Author_Institution
    Dept. of Inf. Manage., Kainan Univ., Taoyuan, Taiwan
  • fYear
    2013
  • fDate
    13-15 Dec. 2013
  • Firstpage
    270
  • Lastpage
    275
  • Abstract
    Image data is becoming more and more popular due to the prevalence of image capture devices. How to retrieve the images effectively and efficiently from a large number of images has been a challenging issue in recent years. To deal with such issue, the major purpose of this paper is to propose a concept- and content-aware image retrieval approach using Depth-First Search (DFS) strategy to conduct effective and efficient image semantic retrieval. For effectiveness and efficiency, since the search space is reduced into specific subspaces, the retrieval cost is decreased and the retrieval quality is increased. For semantic retrieval, our proposed method can detect the potential concepts to satisfy the user´s semantic need. In the experimental result, it reveals that our proposed approach is more effective and efficient than traditional ones using Breadth-First-Search (BFS) strategy.
  • Keywords
    content-based retrieval; image retrieval; tree searching; DFS strategy; concept-aware image retrieval approach; content-aware image retrieval approach; depth-first search strategy; high-performance content-based image semantic retrieval; image capture devices; image data; retrieval cost reduction; retrieval quality improvement; search space; user semantic need satisfaction; Feature extraction; Image color analysis; Image retrieval; Search engines; Semantics; Visualization; Breadth-First-Search; Depth-First Search; content-based image retrieval; semantic image retrieval; text-based image retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2013 IEEE International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/GrC.2013.6740420
  • Filename
    6740420