This paper describes the processing algorithm methodology and preliminary results from a novel optical-based system for the assessment of chemical and mechanical deterioration of artworks. The FP7 Syddarta Project prototype is composed of two optical channels: 1) a 3D imaging channel which acquires 3D surface data and multiband information in the visible spectral range; 2) an infrared hyperspectral imaging channel in the spectral range 900 to 2500 nm. The processing algorithms developed perform the system calibration, damage detection and chemical deterioration analysis. Both photometric and geometric calibrations have been implemented. The photometric calibration is based on a white reference and intensity map and compensates for variation in light intensities. The geometric calibration is based on planar homographies to determine the interior and exterior orientation of the projector and the two cameras. This is used to map the acquired data of the different sensors into a single reference frame. To acquire 3D data, a set of phase-shifted fringe patterns is projected on the object which are processed by Fourier transform. To identify mechanical deterioration, the acquired 3D cloud of points is meshed and differences in surface normals for a given radius are computed. To analyse the chemical deterioration of the pigments a supervised classification method has been implemented. First of all, spectral data is normalized with the Extended Multiplicative Scatter Correction algorithm. Then, data dimensionality is reduced by applying Principal Component Analysis and classification is done with Support Vector Machine. Results are presented showing the performance of the described algorithms.
KEYWORDS: 3D modeling, Clouds, Cameras, Chemical analysis, 3D image processing, 3D image reconstruction, 3D acquisition, Fringe analysis, Calibration, Statistical analysis
Deterioration of artwork, in particular paintings, can be produced by environmental factors such as temperature
fluctuations, relative humidity variations, ultraviolet radiation and biological factors among others. The effects of these
parameters produce changes in both the painting structure and chemical composition. While well established analytical
methodologies, such as those based in Raman Spectroscopy and FTIR Spectroscopy require the extraction of a sample
for its inspection, other approaches such as hyperspectral imaging and 3D scanning present advantages for in-situ, noninvasive
analysis of artwork. In this paper we introduce a novel system and the related methodology to acquire process,
generate and analyze 4D data of paintings. Our system is based on non-contact techniques and is used to develop
analytical tools which extract rich 3D and hyperspectral maps of the objects, which are processed to obtain accurate
quantitative estimations of the deterioration and degradation present in the piece of art. In particular, the construction of
4D data allows the identification of risk maps on the painting representation, which can allow the curators and restorers
in the task of painting state evaluation and prioritize intervention actions.
The SYDDARTA project is an on-going European Commission funded initiative under the 7th Framework Programme. Its main objective is the development of a pre-industrial prototype for diagnosing the deterioration of movable art assets. The device combines two different optical techniques for the acquisition of data. On one hand, hyperspectral imaging is implemented by means of electronically tunable filters. On the other, 3D scanning, using structured light projection and capturing is developed. These techniques are integrated in a single piece of equipment, allowing the recording of two optical information streams. Together with multi-sensor data merging and information processing, estimates of artwork deterioration and degradation can be made. In particular, the resulting system will implement two optical channels (3D scanning and short wave infrared (SWIR) hyperspectral imaging) featuring a structured light projector and electronically tunable spectral separators. The system will work in the VIS-NIR range (400-1000nm), and SWIR range (900-2500nm). It will be also portable and user-friendly. Among all possible art work under consideration, Baroque paintings on canvas and wooden panels were selected as the project case studies.
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