Automatic determination of peroxides and acidity of olive oil using machine vision in olive fruits before milling process

Ones of the most important parameters to measure of olive oil quality are acidity and peroxide index and, currently, they are measured in a laboratory using samples of olives extracted from a batch in the reception process. The aim of this work is to provide an automatic inspection system, based on computer vision-visible and infrared (IR) channels-, to infer automatically these parameters. The proposal uses the differences in superficial textures, the defects in IR pictures and a color estimation in CIELab. Furthermore, a different image preprocessing has been employed and an Artificial Neural Networks have been used as estimation technique. The system has reached good estimation results with R=96.3 in acidity and R=93.9 in peroxide index.