• DocumentCode
    2520967
  • Title

    SIFT algorithm analysis and optimization

  • Author

    Daixian, Zhu

  • Author_Institution
    Commun. & Inf. Eng. Coll., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
  • fYear
    2010
  • fDate
    9-11 April 2010
  • Firstpage
    415
  • Lastpage
    419
  • Abstract
    Due to good invariance of scale, rotation, illumination, SIFT (Scale Invariant Feature Transform) descriptor is commonly used in image matching. The steps of extracting SIFT feature are analyzed in detail, and SIFT Key-point location is optimized. The Chamfer distance is used in this article; it decreases computation time and improves the accuracy of image matching. The experimental results show that the algorithm can reduce time complexity and maintain robust quality at the same time.
  • Keywords
    feature extraction; image matching; optimisation; transforms; Chamfer distance; SIFT algorithm analysis; feature extraction; image matching; optimization; scale invariant feature transform; Algorithm design and analysis; Data mining; Educational institutions; Feature extraction; Image analysis; Image matching; Information analysis; Lighting; Pixel; Robustness; Chamfer distance; Comparability measurement; SIFT; analysis and optimization; image matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Signal Processing (IASP), 2010 International Conference on
  • Conference_Location
    Zhejiang
  • Print_ISBN
    978-1-4244-5554-6
  • Electronic_ISBN
    978-1-4244-5556-0
  • Type

    conf

  • DOI
    10.1109/IASP.2010.5476084
  • Filename
    5476084
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2520967