Real-Time Size and Mass Estimation of Slender Axi-Symmetric Fruit/Vegetable Using a Single Top View Image

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 18; p. 5406
• Main Authors: Huynh, Tri, Tran, Ly, Dao, Son
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 21.09.2020; MDPI AG
• Subjects: Agriculture - methods; Fruit - anatomy & histology; image processing; Image Processing, Computer-Assisted; machine vision; mass estimation; vegetable; Vegetables - anatomy & histology; volume estimation; water displacement method; image processing; water displacement method; fruit; mass estimation; volume estimation; vegetable; machine vision
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20185406

Among the physical attributes of agricultural materials, mass, volume, and sizes have always been important quality parameters. Previous research focused mostly on volume estimation using stereo-based approaches, which rely on manual intervention or require a multiple-cameras set up or multiple-frames captures from different viewing angles to reconstruct the three-dimensional point-cloud information. These approaches are tedious and not suitable for practical machine vision systems. In this work, we only use a single camera mounted on the ceiling of the imaging chamber, which is directly above the fruit/vegetable to capture its top-view, two-dimensional image. We developed a method to estimate the mass/volume of agricultural products with axi-symmetrical shapes such as a carrot or a cucumber. The mass/volume is estimated as the sum of smaller standard blocks, such as chopped pyramids, an elliptical cone, or a conical cone. The computed mass/volume showed good agreement with analytical and experimental results. The weight estimation error is 95% for the case of the carrot and 96.7% for the cucumber. The method proved to be sufficiently accurate, easy to use, and rotationally invariant.