Contrast Marginalised Gradient Template Matching

  • Saleh Basalamah
  • Anil Bharath
  • Donald McRobbie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3023)


This paper addresses a key problem in the detection of shapes via template matching: the variation of accumulator-space response with object-background contrast. By formulating a probabilistic model for planar shape location within an image or video frame, a vector-field filtering operation may be derived which, in the limiting case of vanishing noise, leads to the Hough-transform filters reported by Kerbyson & Atherton [5]. By further incorporating a model for contrast uncertainty, a contrast invariant accumulator space is constructed, in which local maxima provide an indication of the most probable locations of a sought planar shape. Comparisons with correlation matching, and Hough transforms employing gradient magnitude, binary and vector templates are presented. A key result is that a posterior density function for locating a shape marginalised for contrast uncertainty is obtained by summing the functions of the outputs of a series of spatially invariant filters, thus providing a route to fast parallel implementations.


Probability Density Function Template Match Hough Transform Planar Shape Posterior Density Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Saleh Basalamah
    • 1
  • Anil Bharath
    • 1
  • Donald McRobbie
    • 2
  1. 1.Dept. of BioengineeringImperial College LondonLondonUK
  2. 2.Imaging Sciences Dept.Charing Cross Hospital, Imperial CollegeLondonUK

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