Abstract
In this paper we propose an algorithm for the sub-pixel edge detection using a B-spline model. In contrast to the usual methods which are generally sensitive to local perturbations, our approach is based on a global computation of the edge using a Maximum Likelihood rule. In the proposed algorithm the likelihood of the observations is explicitly computed, it ensures the filtering of the noisiest data. Experiments are given and show the adequacy and effectiveness of this algorithm.
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Bouchara, F., Bertrand, M., Ramdani, S., Haydar, M. (2007). Sub-pixel Edge Fitting Using B-Spline. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_32
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DOI: https://doi.org/10.1007/978-3-540-71457-6_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71456-9
Online ISBN: 978-3-540-71457-6
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