Multispectral RTI Capture

MURTIC

Multispectral RTI Capture

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Challenge

In many application fields, it is necessary to acquire shape and color information of surfaces. Reflectance Transformation Imaging (RTI) has emerged in recent years as a very flexible and affordable technique, especially in the field of Cultural Heritage. However, it is still used mostly for qualitative inspections, since repeatable quantitative data capture is achievable only in very controlled settings.

Overview

CRS4 has developed a flexible hardware and software solution for the capture of shape and multispectral material properties using RTI solution. Our novel setup combines a multispectral camera and LED lights with multiple specular targets with a large, planar and diffuse target and introduces calibration methods that jointly exploit these targets to precisely estimate per-pixel light direction and intensity in both fixed and free-form settings. Our prototypes include a full half-dome, a ring and a fully free-form solution. Capture and light components are controlled by Arduino and special electronics to fully automate capturing in the dome and ring situation, and to support interactive capture in the free-form solutions. Tests on targets and a variety of cultural objects (including metal artifacts and paintings) demonstrate important advances with respect to currently available solutions in terms of accuracy and repeatability.

Innovative features

  • Flexible RTI approach supporting many practical implementations, from fully fixed light constellations to moving lights, and from visible light capture to multispectral;
  • Improved accuracy and repeatability through novel autocalibration methods.

Potential users

Researchers in visual computing, cultural heritage experts.

Impact sectors

Cultural Institutions, Museums.

Other resources

  1. Irina Ciortan, Tinsae Dulecha, Andrea GIachetti, Ruggero Pintus, Alberto Jaspe Villanueva, and Enrico Gobbetti. Artworks in the Spotlight: Characterization with a Multispectral Dome. IOP Conference Series: Materials Science and Engineering, 364(1): 012025, 2018.
  2. Andrea Giachetti, Irina Ciortan, Claudia Daffara, Giacomo Marchioro, Ruggero Pintus, and Enrico Gobbetti. A Novel Framework for Highlight Reflectance Transformation Imaging. Computer Vision and Image Understanding, 168: 118-131, 2018.
  3. Andrea Giachetti, Irina Ciortan, Claudia Daffara, Ruggero Pintus, and Enrico Gobbetti. Multispectral RTI Analysis of Heterogeneous Artworks. In The 14th Eurographics Workshop on Graphics and Cultural Heritage. Pages 19-28, September 2017.

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