Deterministic Method for Automatic Visual Grading of Seed Food Products
Résumé
This paper presents a deterministic method for automatic visual grading, designed to solve the industrial problem of evaluation of seed lots. The sample is thrown in bulk onto a tray placed in a chamber for acquiring color image. An image processing method had been developed to separate and characterize each seed. Shape learning is performed on isolated seeds. The collected information is used for the segmentation. A first step is made based on simple criteria such as regions, edges and normals to the boundary. Then, an active contour with shape prior is performed to improve the results.
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