1, Konstantin Sofeikov1, Jeremy Levesley1, Alexander N. Gorban1, Penelope Allison2 and Nicholas J. Cooper31. Department of Mathematics, University of Leicester, UK. Email: i.tyukin@leicester.ac.uk / sofeykov@gmail.com / jl1@leicester.ac.uk / ag153@le.ac.uk
2. School of Archaeology and Ancient History, University of Leicester. Email: pma9@le.ac.uk
3. University of Leicester Archaeological Services (ULAS), School of Archaeology and Ancient History, University of Leicester. Email: njc9@leicester.ac.uk
Cite this as: Tyukin, I., Sofeikov, K., Levesley, J., Gorban, A.N., Allison, P. and Cooper, N.J. 2018 Exploring Automated Pottery Identification [Arch-I-Scan], Internet Archaeology 50. https://doi.org/10.11141/ia.50.11
A hand-held smart device technology (Arch-I-Scan) is currently being developed and tested for scanning and classifying archaeological artefacts. The technology is based on a new platform developed by ARM, jointly with University of Leicester within Innovate UK Knowledge Transfer Partnership project (code KTP009890), and takes advantage of new algorithms for one-trial learning based on measure concentration phenomenon in high dimensions. This article discusses the development of a 'proof of concept' for automating the classification of Roman ceramic vessel types using whole vessels held in the collections of the Jewry Wall Museum, Leicester. The 'proof of concept' illustrates the viability and technical possibility of classifying and discriminating between objects of different types on-the-fly from a limited number of images. This technology is based on recent results (Gorban et al. 2016; Gorban and Tyukin 2017) revealing peculiar geometric properties of finite but large samples of data in high dimension. The ambition is to create a dedicated software that turns commonly available devices such as smart phones or tablets into scanners capable of classifying even small vessel sherds to the correct form and fabric.
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