Non–destructive Detection of Hollow Heart in Potatoes Using Hyperspectral Imaging

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 th...

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Bibliographic Details
Published inComputer Analysis of Images and Patterns pp. 180 - 187
Main Authors Dacal-Nieto, Angel, Formella, Arno, Carrión, Pilar, Vazquez-Fernandez, Esteban, Fernández-Delgado, Manuel
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2011
SeriesLecture Notes in Computer Science
Subjects
Hyperspectral
Infrared
Potato
Random Forest
SVM
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Summary: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.
ISBN:9783642236778
3642236774
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-23678-5_20