Journal
TALANTA
Volume 148, Issue -, Pages 54-61Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2015.10.073
Keywords
Banana; Color features; Firmness; pH; Total soluble solids; Support vector regression
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Banana undergoes significant quality indices and color transformations during shelf-life process, which in turn affect important chemical and physical characteristics for the organoleptic quality of banana. A computer vision system was implemented in order to evaluate color of banana in RGB, Lab and HSV color spaces, and changes in color features of banana during shelf-life were employed for the quantitative prediction of quality indices. The radial basis function (RBF) was applied as the kernel function of support vector regression (SVR) and the color features, in different color spaces, were selected as the inputs of the model, being determined total soluble solids, pH, titratable acidity and firmness as the output. Experimental results provided an improvement in predictive accuracy as compared with those obtained by using artificial neural network (ANN). (C) 2015 Elsevier B.V. All rights reserved.
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