Computer Vision for Laboratory Quality Control on Frozen Fruit
Ricauda Aimonino, D.
Barge, P.
Comba, L.
Gay, P.
Occelli, A.
Tortia, C.
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Ricauda Aimonino D., Barge P., Comba L., Gay P., Occelli A., Tortia C., 2015, Computer Vision for Laboratory Quality Control on Frozen Fruit, Chemical Engineering Transactions, 44, 175-180.
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The appropriate amount of antioxidant compounds added in frozen light-flesh cut fruit production process is usually estimate evaluating colour changes, in particular by measuring the minimum time before browning phenomena occur. This parameter is assessed by visual inspections performed by trained operators: a time consuming and strongly subjective procedure.
The development of a Computer Vision System (CVS) for quality control in frozen fruit slice is presented in this paper. An algorithm to detect and measure browned area on fruit slices was implemented in order to describe colour changes evolution. The red component of browned areas is emphasized by an adequate linear combination of RGB colour channels of digital images, and an entropy-based automatic segmentation is applied to the obtained high contrast grey-scale image. This approach is not based on colour measurement of samples by the CVS, avoiding the colour calibration phase. Antioxidant solutions with different concentrations were applied in order to obtain different browning times and evaluate algorithm performances. Results obtained with the CVS strongly fit with visual inspections performed by trained operators, showing the reliability of the method for this specific application.
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