Online Tomato Inspection Using X-Ray Radiographies and 3- Dimensional Shape Models

Abstract

A method is proposed that fits a 3-dimensional shape model (SM) on X-ray radiographies of tomatoes on a conveyor belt to allow for inspection of internal tomato quality using X-ray. For the training of the SM a set of computed tomography (CT) scans is used. From these scans, the surfaces of the fruits are extracted. Corresponding points on all these surfaces are located after which the variation in position of every point can be determined using principal component analysis (PCA). The result of this process is a mean shape with various modes of variation, which represent the variability of the shape. Any shape can then be reconstructed through a linear combination of the mean shape and its modes of variation. During runtime, the contour of every tomato is extracted onto which the SM is fitted. This allows us to accurately estimate tomato volume and 3-dimensional shape, and assess the presence of defects and other unwanted properties from X-ray radiographies in an online application. Results are promising, but show that improvement can be made by simulating radiographs from the shape model and fitting these directly to the measured radiograph.