• DocumentCode
    2240562
  • Title

    Robust affine invariant matching with application to line features

  • Author

    Tsai, Frank C D

  • Author_Institution
    Courant Inst. of Math. Sci., New York Univ., NY, USA
  • fYear
    1993
  • fDate
    15-17 Jun 1993
  • Firstpage
    393
  • Lastpage
    399
  • Abstract
    Line features in geometric hashing are discussed. Lines are used as the primitive features to compute the geometric invariants, combining the Hough transform with a variation of geometric hashing as a technique for model-based object recognition in seriously degraded single intensity images. The effect of uncertainty of line features on the computed invariants for the case where images are formed under affine viewing transformations is analytically determined. The system is implemented with experiments on polygonal objects, which are modeled by lines. It is shown that the technique is noise resistant and suitable in an environment containing many occlusions
  • Keywords
    Hough transforms; feature extraction; image recognition; image sequences; Hough transform; affine viewing transformations; geometric hashing; geometric invariants; line features; model-based object recognition; noise resistant; polygonal objects; primitive features; robust affine invariant matching; seriously degraded single intensity images; uncertainty; Degradation; Image analysis; Image edge detection; Image segmentation; Layout; Object recognition; Petroleum; Robot sensing systems; Robustness; Solid modeling; Uncertainty; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
  • Conference_Location
    New York, NY
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-3880-X
  • Type

    conf

  • DOI
    10.1109/CVPR.1993.341100
  • Filename
    341100