An Interactive Level Set Approach to Semi-automatic Detection of Features in Food Micrographs

Gaetano Impoco 1 and Giuseppe Licitra 1,2

1 Co.R.Fi.La.C. – Consorzio Ricerca Filiera Lattiero-Casearia, Ragusa, Italy
2 D.A.C.P.A., University of Catania, Italy


Microscopy is often employed in food research to inspect the microstructural features of food samples.  Accurate detection of microscopic features is required for reliable quantitative analysis. We propose a user-assisted approach that can be easily integrated into a graphical interface. The proposed algorithm is based on a fast approximation of the common region-based level set equation, providing interactive computations. Experiments have been run on cheese micrographs acquired with electron and confocal microscopes.

Keywords: level set, segmentation, feature detection, cheese, microstructure.



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Gaetano Impoco