Searching the EAGLE Epigraphic Material Through Image Recognition via a Mobile Device

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9371)


This demonstration paper describes the mobile application developed by the EAGLE project to increase the use and visibility of its epigraphic material. The EAGLE project (European network of Ancient Greek and Latin Epigraphy) is gathering a comprehensive collection of inscriptions (about 80 % of the surviving material) and making it accessible through a user-friendly portal, which supports searching and browsing of the epigraphic material. In order to increase the usefulness and visibility of its content, EAGLE has developed also a mobile application to enable tourists and scholars to obtain detailed information about the inscriptions they are looking at by taking pictures with their smartphones and sending them to the EAGLE portal for recognition. In this demonstration paper we describe the EAGLE mobile application and give an outline of its features and its architecture.


Mobile application Image recognition Similarity search Epigraphy Latin and Greek inscriptions 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    The EAGLE Project.
  2. 2.
    The EAGLE Project, Deliverable D4.1 – Aggregation and Image Retrieval system (AIM) Infrastructure SpecificationGoogle Scholar
  3. 3.
    Gennaro, C., Amato, G., Bolettieri, P., Savino, P.: An approach to content-based image retrieval based on the Lucene search engine library. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds.) ECDL 2010. LNCS, vol. 6273, pp. 55–66. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Jégou, H., Perronnin, F., Douze, M., Sanchez, J., Perez, P., Schmid, C.: Aggregating local image descriptors into compact codes. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(9), 1704–1716 (2012)CrossRefGoogle Scholar
  5. 5.
    Giuseppe, A., Falchi, F., Gennaro, C.: Geometric consistency checks for kNN based image classification relying on local features. In: Proceedings of the Fourth International Conference on SImilarity Search and APplications, pp. 81–88. ACM (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.CNR-ISTIPisaItaly
  2. 2.EurevaParisFrance
  3. 3.Università di Roma La SapienzaRomeItaly

Personalised recommendations