We present a new method to detect the presence of the hollow heart, an internal disorder of the potato tubers, using hyperspectral imaging technology in the infrared region. A set of 468 hyperspectral cubes of images has been acquired from Agria variety potatoes, that have been cut later to check the presence of a hollow heart. We developed several experiments to recognize hollow heart potatoes using different Artificial Intelligence and Image Processing techniques. The results show that Support Vector Machines (SVM) achieve an accuracy of 89.1% of correct classification. This is an automatic and non-destructive approach, and it could be integrated into other machine vision developments. © 2011 Springer-Verlag.
CITATION STYLE
Dacal-Nieto, A., Formella, A., Carrión, P., Vazquez-Fernandez, E., & Fernández-Delgado, M. (2011). Non-destructive detection of hollow heart in potatoes using hyperspectral imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6855 LNCS, pp. 180–187). Springer Verlag. https://doi.org/10.1007/978-3-642-23678-5_20
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