Three-dimensional reconstruction of irregular foodstuffs

Abstract

Three-dimensional reconstruction of general solid food materials was performed using a reverse engineering method based on a surface cross-sectional design. Digital images of cross-sections of irregular multi-dimensional foodstuffs were acquired using a computer vision system, and image processing was performed to obtain the actual boundaries. These boundaries were then approximated by closed B-spline curves, which were assembled through a lofting technique to construct a geometrical representation of food materials. Considering the reconstructed objects, a procedure based on finite element method was developed to estimate the surface area and volume. The developed finite element method approach was validated against experimental volume values of apples and meat pieces, obtaining an estimation error less than 2%. Surface area prediction equations were proposed from estimated surface area values and weight and volume measurements. Good agreement was found with previously reported results.

Using Density Measurement on Semispinalis capitis as a Tool to Determinate the Composition of Pork Meat

“…In the publications on the use of 3D scanning in food examinations, the authors mainly focused their attention primarily on issues of accuracy of product volume estimation. For example, Goñi et al (2007) using 3D scanning technique determined the volume of, e.g., pieces of meat with mean estimation error lower than 2%.…”

“…As an example, Uyar and Erdoğdu (2009) determined that there exists a possibility to use a 3D scanning technique for the determination of volume of food products with irregular shapes, such as bananas, pears, and eggs. Goñi et al (2007) using 3D scanning technique determined the volume of pieces of meat. The 3D scanning method was also used for the determination of cereal product porosity, and the authors underlined the fact that using this method does not require analytic preparation of a sample (Russ 2015).…”

Numerical modelling of agricultural products on the example of bean and yellow lupine seeds

“…Numerical modelling of a product shape based on conventional methods is a laborious process, in particular in products with irregular shape (Goni et al, 2007). Fruit and seed dimensions are very often determined with the use of image analysis software and measuring tools such as calipers and micrometers (Frączek and Wróbel, 2006).…”

Volume estimation of strawberries, mushrooms, and tomatoes with a machine vision system

“…The object is sectioned along a selected axis and section measurements are used to estimate surface area and volume of a reconstructed object. Goñi et al [9] used this method to estimate the surface area and volume of apples and meat pieces with less than 2% estimation error. They concluded that applying lofting technique allows obtaining an accurate representation of the real shape of irregular multi-dimensional foodstuffs and this method demonstrated its ability to correctly predict volume and surface area of general objects, including those of low symmetry and sphericity.…”