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.
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