A new method for accurate, high-throughput volume estimation from three 2D projective images

ABSTRACT

In this article, a new method for estimating the volume of selected fruits and vegetables, using information obtained from three orthogonal images of the object is proposed. The method was based on a novel lower bound on this volume, combined with an application of a well-known upper bound. The lower bound was obtained by calculating the volume of an artificial object created from the intersection of the three object silhouettes. The method was applied to a significant range of food products and simple geometric objects, and it was found that the method estimated volume with approximately 11.9% error, generally, and 2%, for rounded objects, specifically.

KEYWORDS:

• High throughput
• Biomass
• Phenotyping
• Upper and lower bounds
• Volume estimation

Acknowledgments

The authors would like to thank Dr. Jorge Aarao for valuable discussions.

Funding

This project is supported with funding from the Grains Research and Development Corporation, Australia.

Additional information

Funding

This project is supported with funding from the Grains Research and Development Corporation, Australia.