Volumetric estimation using 3D reconstruction method for grading of fruits

Abstract

Grading of the fruits is one of the important post harvest tasks that the fruit processing agro-industries do. Although the internal quality of the fruit is important, the external quality of the fruit influences the consumers and the market price significantly. External quality of the fruit is based on the features such as color, maturity, shape, texture and size of the fruit. Apart from being expensive and time consuming, the manual grading process may face challenges such as subjectivity in grading, inconsistency and non-availability of the experts during peak seasons. On the other hand, computer vision based fruit grading systems using 2D techniques do not consider self occluding surface of the fruit and fail to determine the percentage of the matured region accurately. The grading systems which approximate the shape of the fruit to a known geometrical shape fail to compute the volume of the fruits with arbitrary shapes accurately. This paper presents a nondestructive and accurate fruit grading system based on the volume and maturity feature implemented using Fuzzy Rule Based Classifier (FRBC). The system estimates the volume of the fruit using volumetric 3D reconstruction method in multiple-camera environment and computes the percentage of the matured region of the fruit with high accuracy. The experimental results show that the accuracy of the proposed grading system in volume estimation and fruit grading is 98.5%. The ability of the proposed 3D reconstruction method to reconstruct the fruits with arbitrary shapes makes the grading system more robust and dynamic.