A framework for analysis of large database of old art paintings

Jérome Da Rugna; Gaël Chareyron; Ruven Pillay; Morwena Joly

doi:10.1117/12.872500

8 March 2011 A framework for analysis of large database of old art paintings

Jérome Da Rugna, Gaël Chareyron, Ruven Pillay, Morwena Joly

Proceedings Volume 7869, Computer Vision and Image Analysis of Art II; 786907 (2011) https://doi.org/10.1117/12.872500
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

For many years, a lot of museums and countries organize the high definition digitalization of their own collections. In consequence, they generate massive data for each object. In this paper, we only focus on art painting collections. Nevertheless, we faced a very large database with heterogeneous data. Indeed, image collection includes very old and recent scans of negative photos, digital photos, multi and hyper spectral acquisitions, X-ray acquisition, and also front, back and lateral photos. Moreover, we have noted that art paintings suffer from much degradation: crack, softening, artifact, human damages and, overtime corruption. Considering that, it appears necessary to develop specific approaches and methods dedicated to digital art painting analysis. Consequently, this paper presents a complete framework to evaluate, compare and benchmark devoted to image processing algorithms.

Citation Download Citation

Jérome Da Rugna, Gaël Chareyron, Ruven Pillay, and Morwena Joly "A framework for analysis of large database of old art paintings", Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 786907 (8 March 2011); https://doi.org/10.1117/12.872500

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