Image Analysis and Processing – ICIAP 2011

Volume 6979 of the series Lecture Notes in Computer Science pp 303-312

Common Scab Detection on Potatoes Using an Infrared Hyperspectral Imaging System

  • Angel Dacal-NietoAffiliated withComputer Science Department, Universidade de Vigo
  • , Arno FormellaAffiliated withComputer Science Department, Universidade de Vigo
  • , Pilar CarriónAffiliated withComputer Science Department, Universidade de Vigo
  • , Esteban Vazquez-FernandezAffiliated withGRADIANT, Galician R&D Center in Advanced Telecommunications
  • , Manuel Fernández-DelgadoAffiliated withCentro de Investigación en Tecnoloxías da Información (CITIUS), Universidade de Santiago de Compostela

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The common scab is a skin disease of the potato tubers that decreases the quality of the product and influences significantly the price. We present an objective and non-destructive method to detect the common scab on potato tubers using an experimental hyperspectral imaging system. A supervised pattern recognition experiment has been performed in order to select the best subset of bands and classification algorithm for the problem. Support Vector Machines (SVM) and Random Forest classifiers have been used. We map the amount of common scab in a potato tuber by classifying each pixel in its hyperspectral cube. The result is the percentage of the surface affected by common scab. Our system achieves a 97.1% of accuracy with the SVM classifier.


Hyperspectral Infrared Potato SVM Random Forest