Special Issue "Fine Art Pattern Extraction and Recognition"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: 28 February 2021.

Special Issue Editors

Prof. Giovanna Castellano
Guest Editor
Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4-70125 Bari, Italy
Interests: image processing; computer vision; fuzzy systems; fuzzy clustering; image retrieval; neural networks; neuro-fuzzy modeling; granular computing; recommender systems
Special Issues and Collections in MDPI journals
Dr. Gennaro Vessio
Guest Editor
Department of Computer Science, University of Bari, Italy
Interests: machine learning; deep learning; pattern recognition; computer vision; health informatics; biometrics
Special Issues and Collections in MDPI journals
Dr. Fabio Bellavia
Guest Editor
Department of Math and Computer Science, University of Palermo, Italy
Interests: computer vision; image processing; image matching; 3D reconstruction; image mosaicing; color correction

Special Issue Information

Dear Colleagues,

Cultural heritage, in particular fine art, has invaluable importance for the cultural, historic, and economic growth of our societies. Fine art is developed primarily for aesthetic purposes, and it is mainly concerned with paintings, sculptures, and architectures. In the last few years, due to technology improvements and drastically declining costs, a large-scale digitization effort has been made, leading to a growing availability of large digitized fine art collections. This availability, along with the recent advancements in pattern recognition and computer vision, has opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand fine arts. Among the other benefits, a deeper understanding of fine arts has the potential to make them more accessible to a wider population, both in terms of fruition and creation, thus supporting the spread of culture.

The ability to recognize meaningful patterns in fine art inherently falls within the domain of human perception, and this perception can be extremely hard to conceptualize. Thus, visual-related features, such as those automatically learned by deep learning models, can be the key to tackling problems of extracting useful representations from low-level colour and texture features. These representations can assist in various art-related tasks, ranging from object detection in paintings to artistic style categorization, useful for examples in museum and art gallery websites.

The aim of the International Workshop on Fine Art Pattern Extraction and Recognition (FAPER 2020 @ ICPR 2020) is to provide an international forum for those who wish to present advancements in the state of the art, innovative research, ongoing projects, and academic and industrial reports on the application of visual pattern extraction and recognition for the better understanding and fruition of fine arts. The workshop solicits contributions from diverse areas such as pattern recognition, computer vision, artificial intelligence, and image processing.

This Special Issue welcomes selected papers from FAPER 2020. In addition, we also solicit contributions from scholars involved and interested in this research area.

Prof. Giovanna Castellano
Dr. Gennaro Vessio
Dr. Fabio Bellavia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Application of machine learning and deep learning to cultural heritage
  • Computer vision and multimedia data
  • Generative adversarial networks for artistic data
  • Augmented and virtual reality for cultural heritage
  • 3D reconstruction of historical artifacts
  • Historical document analysis
  • Content-based retrieval in the art domain
  • Speech, audio, and music analysis from historical archives
  • Digitally enriched museum visits
  • Smart interactive experiences in cultural sites
  • Projects, products, or prototypes for cultural heritage restoration, preservation, and fruition

Published Papers (1 paper)

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Open AccessArticle
A Portable Compact System for Laser Speckle Correlation Imaging of Artworks Using Projected Speckle Pattern
J. Imaging 2020, 6(11), 119; https://doi.org/10.3390/jimaging6110119 - 06 Nov 2020
Artworks have a layered structure subjected to alterations caused by various factors. The monitoring of defects at sub-millimeter scale may be performed by laser interferometric techniques. The aim of this work was to develop a compact system to perform laser speckle imaging in [...] Read more.
Artworks have a layered structure subjected to alterations caused by various factors. The monitoring of defects at sub-millimeter scale may be performed by laser interferometric techniques. The aim of this work was to develop a compact system to perform laser speckle imaging in situ for effective mapping of subsurface defects in paintings. The device was designed to be versatile with the possibility of optimizing the performance by easy parameters adjustment. The system exploits a laser speckle pattern generated through an optical diffuser and projected onto the artworks and image correlation techniques for the analysis of the speckle intensity pattern. A protocol for the optimal measurement was suggested, based on calibration curves for tuning the mean speckle size in the acquired intensity pattern. The system was validated in the analysis of detachments in an ancient painting model using a short pulse thermal stimulus to induce a surface deformation field and standard decorrelation algorithms for speckle pattern matching. The device is equipped with a compact thermal camera for preventing any overheating effects during the phase of the stimulus. The developed system represents a valuable nondestructive tool for artwork diagnostics, allowing the monitoring of subsurface defects in paintings in out-of-laboratory environment. Full article
(This article belongs to the Special Issue Fine Art Pattern Extraction and Recognition)
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