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Mismanagement during postharvest handling of cassava can degrade the quality of the product and depreciate its selling price considerably. This study proposed the feasibility of using RGB-depth camera to measure the quality of cassava roots in a non-destructive, fast and cost-effective manner. Methodology to estimate the volume of cassavas Kasetsart 50 variety was the focus of this study. Using RGB-D images collected from 60 cassava samples with each one being photographed from 6 different orientations. Image Processing model and Point Cloud image model were used to find the volume from depth images, and then disk method and box method were used to estimate the volume of cassava under ellipsoidal shape. Both estimation methods provided usable values for the volumes in the range of 100 - 500 ml with RMSE values of 5.91% and 4.02%, respectively. The estimated volume can be applied to find density to predict the rotten cassava for improving quality and efficiency of cassava industry.

Volume estimation of cassava using consumer-grade RGB-D camera