Pubblicazioni

Autori:

Righetto, L; Gobbetti, E; Ponchio, F; Traviglia, A; De Bernardin, M; Giachetti, A

Titolo:

Ancient coins' surface inspection with web-based neural RTI visualization

Anno:

2023

Tipologia prodotto:

Contributo in atti di convegno

Tipologia ANVUR:

Contributo in Atti di convegno

Lingua:

Inglese

Nome rivista:

PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING

ISSN Rivista:

0277-786X

N° Volume:

12620

Titolo del Convegno:

SPIE Optical Metrology, 2023, Optics for Arts, Architecture, and Archaeology (O3A) IX

Luogo:

Munich

Periodo:

2023

Intervallo pagine:

1-10

Parole chiave:

Neural relighting; web-based visualization

Breve descrizione dei contenuti:

The use of neural encodings has the potential to replace the commonly used polynomial fitting in the analysis of artwork surface based on Reflectance Transformation Imaging (RTI), as it has proved to result in more compact encoding with better relight quality, but it is still not widely used due to the lack of efficient implementations available to practitioners.In this work, we describe an optimized system to encode/decode neural relightable images providing interactive visualization in a web interface allowing multi-layer visualization and annotation. To develop it, we performed several experiments testing different decoder architectures and input processing pipelines, evaluating the quality of the results on specific benchmarks to find the optimal tradeoff between relighting quality and efficiency. A specific decoder has been then implemented for the web and integrated into an advanced visualisation tool. The system has been tested for the analysis of a group of ancient Roman bronze coins that present scarce readability and varying levels of preservation and that have been acquired with a multispectral light dome. Their level of corrosion and degradation, which in some cases hinders the recognition of the images, numerals, or text represented on them, makes the system testing particularly challenging and complex. Testing on such a real case scenario, however, enables us to determine the actual improvement that this new RTI visualization tool can offer to numismatists in their ability to identify the coins.

Pagina Web:

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12620/2674888/Ancient-coins-surface-inspection-with-web-based-neural-RTI-visualization/10.1117/12.2674888.short

Id prodotto:

138783

Handle IRIS:

11562/1123167

ultima modifica:

6 maggio 2024

Citazione bibliografica:

Righetto, L; Gobbetti, E; Ponchio, F; Traviglia, A; De Bernardin, M; Giachetti, A, Ancient coins' surface inspection with web-based neural RTI visualization in «PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING» vol. 12620  in Proc. SPIE 12620, Optics for Arts, Architecture, and Archaeology (O3A) IX, 126200D , Atti di "SPIE Optical Metrology, 2023, Optics for Arts, Architecture, and Archaeology (O3A) IX" , Munich , 2023 , 2023 , pp. 1-10

Consulta la scheda completa presente nel repository istituzionale della Ricerca di Ateneo