Automatic classification of ceramic sherds with relief motifs

Teddy Debroutelle; Sylvie Treuillet; Aladine Chetouani; Matthieu Exbrayat; Lionel Martin; Sebastien Jesset

doi:10.1117/1.JEI.26.2.023010

24 March 2017 Automatic classification of ceramic sherds with relief motifs

Teddy Debroutelle, Sylvie Treuillet, Aladine Chetouani, Matthieu Exbrayat, Lionel Martin, Sebastien Jesset

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 2, 023010 (March 2017). https://doi.org/10.1117/1.JEI.26.2.023010

Abstract

A large corpus of ceramic sherds dating from the High Middle Ages has been extracted in Saran (France). The sherds have an engraved frieze made by the potter with a carved wooden wheel. These relief patterns can be used to date the sherds in order to study the diffusion of ceramic production. The aim of the ARCADIA project was to develop an automatic classification of this archaeological heritage. The sherds were scanned using a three-dimensional (3-D) laser scanner. After projecting the 3-D point cloud onto a depth map, the local variance highlighted the shallow relief patterns. The saliency region focused on the motif was extracted by a density-based spatial clustering of FAST points. An adaptive thresholding was then applied to the depth to obtain a binary pattern close to manual sampling. The five most representative types of motif were classified by training an SVM model with a pyramid histogram of visual words descriptor. Compared with other state-of-the-art methods, the proposed approach succeeded in classifying up to 84% of the binary patterns on a dataset of 377 scanned sherds. The automatic method is extremely time-saving compared to manual stamping.

Citation Download Citation

Teddy Debroutelle, Sylvie Treuillet, Aladine Chetouani, Matthieu Exbrayat, Lionel Martin, and Sebastien Jesset "Automatic classification of ceramic sherds with relief motifs," Journal of Electronic Imaging 26(2), 023010 (24 March 2017). https://doi.org/10.1117/1.JEI.26.2.023010

Received: 7 July 2016; Accepted: 7 March 2017; Published: 24 March 2017

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available