• DocumentCode
    186779
  • Title

    Fast image retrieval with grid-based keypoint detector and binary descriptor

  • Author

    SuGil Choi ; Seungwan Han

  • Author_Institution
    Software Contents Res. Lab., Electron. & Telecommun. Res. Inst., Daejeon, South Korea
  • fYear
    2014
  • fDate
    22-24 Oct. 2014
  • Firstpage
    679
  • Lastpage
    680
  • Abstract
    As an alternative to vector-based descriptors, such as SIFT and SURF, more computationally efficient binary descriptors, such as BRISK and ORB, have recently been proposed. These binary descriptors are usually used in combination with a novel scale-space FAST-based detector to be suitable for real-time applications, but it consumes more time than creating binary descriptors. Therefore, if accuracy can be kept similar, keypoint sampling by a grid is better than FAST-based detector because it consumes almost no time. In this paper, grid-based sampling and BRISK keypoint detector are tested for image retrieval. Experimental results demonstrate that grid-based sampling out performs keypoint detector in terms of accuracy and processing speed.
  • Keywords
    image retrieval; sampling methods; BRISK keypoint detector; ORB; SIFT; SURF; binary descriptor; grid-based keypoint detector; grid-based sampling; image retrieval; keypoint sampling; scale-space FAST-based detector; vector-based descriptor; Accuracy; Computational efficiency; Computer vision; Detectors; Image retrieval; Real-time systems; Visualization; binary descriptor; grid-based sampling; image retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technology Convergence (ICTC), 2014 International Conference on
  • Conference_Location
    Busan
  • Type

    conf

  • DOI
    10.1109/ICTC.2014.6983253
  • Filename
    6983253