Development and an Application of Computer Vision System for Nondestructive Physical Characterization of Mangoes

Abstract

This research reports the comparison study of manual (digital vernier caliper, DVC) method and application of computer vision system (CVS) for evaluation of size attributes (length, width and thickness) of two mango cultivars (Chausa and Dashehari). The color RGB (red, green and blue) camera was used in CVS for capturing of required profile image of fruit. The profile image was then processed and developed algorithms for image analysis and extraction of fruit’s quality attributes. Various morphological features such as area, perimeter, Max Feret diameter (MFD), hydraulic radius, Waddel disk diameter (WDD), elongation factor, compactness factor, Heywood circulatory factor and type factor of both cultivars were also evaluated using developed algorithms and attempted to describe the morphology of the outline and shape of the biological object. Area, perimeter, Max Feret diameter and Waddel disk diameter, further, correlated with the weight and volume of fruit. Various multilinear regression (MLR) models were developed for determining weight and volume of mango fruit of both cultivars using dimensional characteristics (length, width and thickness) of mango fruit evaluated by CVS. The major diameter (single variable) and all three (major, intermediate and minor) diameter (multiple variables)-based models were identified as the best models. Similarly, CVS has yielded above 97.9%, 93.5% and 92.5% accuracy in estimating mango fruits major, intermediate and minor diameters of both cultivars.