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Using Canny's criteria to derive a recursively implemented optimal edge detector


A highly efficient recursive algorithm for edge detection is presented. Using Canny's design [1], we show that a solution to his precise formulation of detection and localization for an infinite extent filter leads to an optimal operator in one dimension, which can be efficiently implemented by two recursive filters moving in opposite directions. In addition to the noise truncature immunity which results, the recursive nature of the filtering operations leads, with sequential machines, to a substantial saving in computational effort (five multiplications and five additions for one pixel, independent of the size of the neighborhood). The extension to the two-dimensional case is considered and the resulting filtering structures are implemented as two-dimensional recursive filters. Hence, the filter size can be varied by simply changing the value of one parameter without affecting the time execution of the algorithm. Performance measures of this new edge detector are given and compared to Canny's filters. Various experimental results are shown.

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Deriche, R. Using Canny's criteria to derive a recursively implemented optimal edge detector. Int J Comput Vision 1, 167–187 (1987).

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  • Time Execution
  • Computer Vision
  • Computer Image
  • Optimal Operator
  • Computational Effort