75885 - Image Processing and Virtual Restoration

Learning outcomes

The student will learn the critical use of IT tools for the editing and processing of digital images of artwork, including diagnostics at different frequency bands, virtual-reality simulations, virtual restoration, based on the fundamental knowledge of the degrade and conservation of cultural heritage. The student will learn the basics of digital representation of historical and artistic contents, and will be able to prepare a digital presentation focused on an evaluation of the restoration quality.

Course contents

The course is divided into three parts with different teaching methods: class lectures, blended learning and lab exercises.

1) Technical and scientific fundaments of the digital communication; notion of virtual or digital restoration and the related critical debate; digital tools in the field of the history of the book and document. This section will be taught though class-base seminars on relevant case studies concerning the documentation, analysis and restoration of digital manuscripts, print works, palimpsests and historical cartography.

2) Digital representation of images, raster and vector formats; tech specs for archives and dissemination. This blended learning section will include tutorials and online handouts, and represents an essential requisite for the following section.

3) Specific software for documentation, analysis and digital restoration; critical evaluation of different software (proprietary and open source) aimed at hands-on image editing. This (at least) 15-hour section will be based on exercises at the Frame Lab of the Department of Beni Culturali (details to be defined during the course).

Readings/Bibliography

Part 1.
Required: J.F. Llyotard, La condizione post-moderna. Rapporto sul sapere, trad. it. Milano: Feltrinelli, 2002 nonché di A. Salarelli, Introduzione alla scienza dell’informazione, Milano: Bibliografica, 2012.

Virtual restoration and debate: G. Bianco et al., ‘A framework for virtual restoration of ancient documents by combination of multispectral and 3D imaging’, in E. Puppo, A. Brogni, L. De Floriani (eds.), Eurographics Italian Chapter Conference, 2010 <URI: http://dx.doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2010/001-007>

A. Giacometti et al., ‘The value of critical destruction: Evaluating multispectral image processing methods for the analysis of primary historical texts’ in Digital scholarship in the Humanities 6, October 2015, <DOI: http://dx.doi.org/10.1093/llc/fqv036>

Case studies: digital resources will be provided during the lectures.

Part 2
In addition to the materials available from the course website: R.C. Gonzalez, R.E. Woods, Elaborazione delle immagini digitali, 3. ed., Milano: Pearson, 2008 (chs. 1, 2, 6, 8); M. Lazzari, Informatica umanistica, Milano: MacGraw-Hill, 2014 (ch. 3, pp. 66-69).

Part 3
Software handbooks or tutorials will be discussed during the lab exercises.

Teaching methods

Class seminars, e-learning classes, and exercises at the Frame LAB of the Department of Beni Culturali will address each of the course topics.

Assessment methods

Oral examination of the skills regarding the digital analysis of the manuscript and print materials. Additionally, the student will prepare a digital restoration or analysis project, to be agreed upon with the lecturer. Marking criteria:

- Fail: insufficient knowledge of the course topics; methodological mistakes/lack of originality of the project.

- Pass: adequate knowledge of the course topics; adequate project.

- Merit: good knowledge of the course topics; good project, including sufficient structural complexity.

- Distinction: excellent and engaged knowledge of the course topics. The project features methodological coherency, structural complexity and identity, and fully meets the course topics.

Teaching tools

Oral examination of the skills regarding the digital analysis of the manuscript and print materials. Additionally, the student will prepare a digital restoration or analysis project, to be agreed upon with the lecturer. Marking criteria:

- Fail: insufficient knowledge of the course topics; methodological mistakes/lack of originality of the project.

- Pass: adequate knowledge of the course topics; adequate project.

- Merit: good knowledge of the course topics; good project, including sufficient structural complexity.

- Distinction: excellent and engaged knowledge of the course topics. The project features methodological coherency, structural complexity and identity, and fully meets the course topics.

Links to further information

https://elearning-cds.unibo.it/course/view.php?id=9428

Office hours

See the website of Alessandro Iannucci