Abstract
The multiscale techniques for edge detection aim to combine the advantages of small and large scale methods, usually by blending their results. In this work we introduce a method for the multiscale extension of the Gravitational Edge Detector based on a t-norm T. We smoothen the image with a Gaussian filter at different scales then perform inter-scale edge tracking. Results are included illustrating the improvements resulting from the application of the multiscale approach in both a quantitative and a qualitative way.
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Lopez-Molina, C., De Baets, B., Bustince, H., Barrenechea, E., Galar, M. (2011). Multiscale Extension of the Gravitational Approach to Edge Detection. In: Lozano, J.A., Gámez, J.A., Moreno, J.A. (eds) Advances in Artificial Intelligence. CAEPIA 2011. Lecture Notes in Computer Science(), vol 7023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25274-7_29
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DOI: https://doi.org/10.1007/978-3-642-25274-7_29
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