Estimation of Volume and Mass of Axi-Symmetric Fruits Using Image Processing Technique

Abstract

This article describes an image processing based technique used to estimate the relationship between volume and mass of axi-symmetric fruits like apple, sweet-lime, lemon, and orange. The technique used a single camera to capture five different views of a fruit. The volume of the fruits was estimated based on its shape. The fruits were categorized into spherical, ellipsoid, and paraboloid shapes and an appropriate analytical model for calculating volume was used for each category. The volume computed was in accordance with the actual volume determined by water displacement method. The average densities measured were 0.808 g/cm³ for apples, 0.912 g/cm³ for sweet-limes, 0.912 g/cm³ for lemons, and 0.814 g/cm³ for oranges. As the density of a particular fruit within a batch was fairly constant, there was a good correlation between the volume and mass of fruits. This hypothesis was used to determine the mass of the fruits based on the estimated volume. Thus with a simple approach used to estimate the volume using a single camera, it was also possible to find the mass of the fruits. The proposed techniques were implemented using C++ language and open source computer vision library and the results were found to be reasonably accurate.

Keywords:

• Volume estimation
• Mass estimation
• Axi-symmetric fruits
• Computer vision
• Image processing