Gradient based progressive probabilistic Hough transform

نویسندگان

  • C. Galambos
  • J. Kittler
  • J. Matas
چکیده

The authors look at the benefits of exploiting gradient information to enhance the progressive probabilistic Hough transform (PPHT). It is shown that using the angle information in controlling the voting process and in assigning pixels to a line, the PPHT performance can be significantly improved. The performance gains are assessed in terms of repeatability of results, a measure that has direct relevance for its use in many applications. The overall improvement in output quality is shown to be greater than that found for the standard Hough transform using the same information. The improved algorithm gives results very close to those of the standard Hough transform, but requires significantly less computation.

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تاریخ انتشار 2004