B. Muik, B. Lendl, A. Molina-Diaz, D. Ortega-Calderon and M. J. Ayora-Canada, “Discrimination of Olives According to Fruit Quality Using Fourier Transform Raman Spectroscopy and Pattern Recognition Techniques,” Journal of Agricultural and Food Chemistry, Vol. 52, No. 20, 2004, pp. 6055-6060.

has been cited by the following article:

• TITLE: Using a Visible Vision System for On-Line Determination of Quality Parameters of Olive Fruits

  AUTHORS: Elena Guzmán, Vincent Baeten, Juan Antonio Fernández Pierna, José A. García-Mesa

  KEYWORDS: On-Line; Algorithm; Maturity Index; Olive Fruit; Image Analysis

  JOURNAL NAME: Food and Nutrition Sciences, Vol.4 No.7A, July 5, 2013

  ABSTRACT: The increased expectations for food products of high quality and safety standards and the need for accurate, fast and objective quality determination of these characteristics in food products continue to grow. In this situation, new techniques are necessary to enable on-line control of quality parameters. Computer vision provides one alternative for an automated, non-destructive and cost-effective technique in order to accomplish these requirements. The maturity index and sanitary conditions were objectively assessed on-line by image analysis obtained through machine vision, in which algorithms of colour-based segmentation, as well as the main operators to detect edges were used. The proposed methodology is able to estimate the maturity index and the percentage of defects in olives. In addition, this system can be potentially used on-line in the classification of olives, which means that it could help to improve the quality control of olive oil in factories.