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In 2018, 47% of global internet users had purchased footwear products through the internet, making it the second most popular online shopping category worldwide right after clothing with 57%. In the same year, on average, about every sixth parcel delivered in Germany (16.3%) was returned. With the effort and costs that are associated with the return of shoes, the objective of reducing the number of returns for shoes promises an enormous economic potential and helps to reduce the CO 2  emissions due to a lower traffic volume. This paper presents a workflow for determining the inside volume surface of shoes using industrial x-ray computed tomography (CT). The fundamental idea is based on the Region Growing (RG) method for the segmentation of the shoe’s inner volume. Experiments are performed to illustrate the correlation of image quality and segmentation result. After obtaining the 3D surface model of an individual foot, the inner volume surface data of a scanned shoe can then be registered and evaluated in order to provide a reliable feedback for the customer regarding the accuracy of fit of a shoe and the individual foot on the basis of an overall ‘metric of comfort’ before buying online. This step is not part of the work at hand. Conclusions are drawn and suggestions for improving the robustness and the flexibility of the workflow are given, so it can be adapted to various shoe types and implemented in a fully automated measurement process in the future.

Generation of a 3D model of the inside volume of shoes for e-commerce applications using industrial x-ray computed tomography