• DocumentCode
    3239229
  • Title

    Phase Invariant Keypoint Detection

  • Author

    Bharath, Anil Anthony ; Kingsbury, Nick

  • Author_Institution
    Imperial Coll. London, London
  • fYear
    2007
  • fDate
    1-4 July 2007
  • Firstpage
    447
  • Lastpage
    450
  • Abstract
    This paper introduces extensions to the complex wavelet keypoint detection paper [1], Keypoints are generated by finding local peaks in accumulated, interpolated maps of the product of magnitudes of directional complex filter responses, as in earlier work. Gradient vector fields derived from these maps are used for keypoint scale characterisation, but this is now performed so as to remove the directionality of gradient field sampling, thereby improving the stability of scale estimates. A new class of keypoints is also introduced: the circular measure (CM) keypoints, which are used to augment the locations found by the filter magnitude product (FMP) keypoints. This new keypoint class generates a higher proportion of keypoints in the interiors of objects, whilst simultaneously providing approximate object scale information, and appears appropriate for directing the attention of a vision system to the interiors of well-defined regions.
  • Keywords
    filtering theory; gradient methods; image sampling; interpolation; object detection; directional complex filter; filter magnitude product; gradient field sampling; phase invariant keypoint detection; Biomedical engineering; Educational institutions; Filtering; Filters; Frequency; Image processing; Phase detection; Robustness; Solids; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing, 2007 15th International Conference on
  • Conference_Location
    Cardiff
  • Print_ISBN
    1-4244-0882-2
  • Electronic_ISBN
    1-4244-0882-2
  • Type

    conf

  • DOI
    10.1109/ICDSP.2007.4288615
  • Filename
    4288615