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- W1982169922 abstract "Recent developments in edge detection have exposed diiferent criteria to gauge the performance of edge detectors in the presense of noise. One of the criteria is Localization, which is the ability of the edge detector to produce from noisy data a detected edge that is as close as possible to the true edge in the image. In this paper, we show the limitation of the localization criteria as previously formulated and propose an alternative. This new performance measure is based on the theory of zero-crossings of stochastic processes. We show that the derivative of a Gaussian is the optimal edge detector for this new measure." @default.
- W1982169922 created "2016-06-24" @default.
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- W1982169922 date "1990-06-01" @default.
- W1982169922 modified "2023-09-23" @default.
- W1982169922 title "<title>Localization performance measure and optimal edge detection</title>" @default.
- W1982169922 doi "https://doi.org/10.1117/12.19530" @default.
- W1982169922 hasPublicationYear "1990" @default.
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