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Issue No.02 - February (2010 vol.32)
pp: 242-257
Olivier Laligant , Université de Bourgogne, Le Creusot
Frédéric Truchetet , Université de Bourgogne, Le Creusot
This paper presents a nonlinear derivative approach to addressing the problem of discrete edge detection. This edge detection scheme is based on the nonlinear combination of two polarized derivatives. Its main property is a favorable signal-to-noise ratio ({SNR}) at a very low computation cost and without any regularization. A 2D extension of the method is presented and the benefits of the 2D localization are discussed. The performance of the localization and {SNR} are compared to that obtained using classical edge detection schemes. Tests of the regularized versions and a theoretical estimation of the {SNR} improvement complete this work.
Edge detection, regularization filter, edge localization, edge model, neighbor edge, discrete approach, nonlinear derivative, noises, performance measure.
Olivier Laligant, Frédéric Truchetet, "A Nonlinear Derivative Scheme Applied to Edge Detection", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.32, no. 2, pp. 242-257, February 2010, doi:10.1109/TPAMI.2008.282
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