Weight Estimation of Mango from Single Visible Fruit Surface using Computer Vision

This paper presents the development of an image processing algorithm to estimate the weight and volume of the mango. In this study, a total of 24 mangoes are used as samples. On account of simplicity, only a single web camera is used to capture the top view image of the mango. From this image, geometric features of the mango such as area, width and length are evaluated. Area of the mango's visible surface is determined by using curve fitting and area between the two curves method. Thickness of the mango, which is not visible in top view image, is necessary to estimate weight and volume more accurately. The required thickness value is calculated from the correlation equation between width and thickness. The thickness variation along the mango length is modelled as an ellipse function. The total estimated volumes of the mango is calculated by using the sum of volumes of transverse sectional elliptic cylinders method. The estimated results are compared with actual measured values. The average accuracy of this algorithm is 95% for both volume and weight estimation. Average processing time for each mango is 0.2 seconds.