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<p>The localization performance measure of edge detectors is addressed. A one-dimensional formulation of the problem is considered. A linear space-invariant filter is used for the detection. The locations of local maxima in the thresholded output of the filter are declared to be the edges. The limitations of conventional performance measures are shown, and a localization performance measure for edge detection is suggested. This performance measure is based on the theory of zero-crossings of stochastic processes. It is shown that the derivative of a Gaussian is the optimal edge detector for the measure.</p>
pattern recognition; localization performance measure; edge detection; linear space-invariant filter; local maxima; zero-crossings; stochastic processes; filtering and prediction theory; optimisation; pattern recognition; picture processing; stochastic processes
R.J.P. deFigueiredo, H.D. Tagare, "On the Localization Performance Measure and Optimal Edge Detection", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 12, no. , pp. 1186-1190, December 1990, doi:10.1109/34.62607
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