Spectral information to get beyond color in the analysis of water-soluble varnish degradation

Martínez-Domingo, Miguel Ángel; Valero, Eva M.; Huertas, Rafael; Durbán, Maŕıa; Espejo, Teresa; Blanc, Rosario

doi:10.1186/s40494-019-0323-5

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Also, the prediction of object appearance variation under a wide range of illuminants is possible through having access to the spectral reflectance of the object. This approach has been applied in computer aided design (CAD) [1], illumination design for museums [2] or characterization of the degradation process of the varnishes on artworks [3]. In addition, applications as diverse as realistic image synthesis using computer graphics [4] or the estimation of surface temperature exposed to sunlight [5], also rely on the input of spectral information.…”

Section: Introductionmentioning

confidence: 99%

Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

Amiri

García-Nieto

Morillas

et al. 2020

Sensors

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In this work, we address the problem of spectral reflectance recovery from both CIEXYZ and RGB values by means of a machine learning approach within the fuzzy logic framework, which constitutes the first application of fuzzy logic in these tasks. We train a fuzzy logic inference system using the Macbeth ColorChecker DC and we test its performance with a 130 sample target set made out of Artist’s paints. As a result, we obtain a fuzzy logic inference system (FIS) that performs quite accurately. We have studied different parameter settings within the training to achieve a meaningful overfitting-free system. We compare the system performance against previous successful methods and we observe that both spectrally and colorimetrically our approach substantially outperforms these classical methods. In addition, from the FIS trained we extract the fuzzy rules that the system has learned, which provide insightful information about how the RGB/XYZ inputs are related to the outputs. That is to say that, once the system is trained, we extract the codified knowledge used to relate inputs and outputs. Thus, we are able to assign a physical and/or conceptual meaning to its performance that allows not only to understand the procedure applied by the system but also to acquire insight that in turn might lead to further improvements. In particular, we find that both trained systems use four reference spectral curves, with some similarities, that are combined in a non-linear way to predict spectral curves for other inputs. Notice that the possibility of being able to understand the method applied in the trained system is an interesting difference with respect to other ’black box’ machine learning approaches such as the currently fashionable convolutional neural networks in which the downside is the impossibility to understand their ways of procedure. Another contribution of this work is to serve as an example of how, through the construction of a FIS, some knowledge relating inputs and outputs in ground truth datasets can be extracted so that an analogous strategy could be followed for other problems in color and spectral science.

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Section: Introductionmentioning

confidence: 99%

Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

Amiri

García-Nieto

Morillas

et al. 2020

Sensors

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“…New portable and fast imaging devices, together with powerful computers, enable researchers to retrieve valuable information from spectral images. Within the field of spectral imaging, applications related to art and cultural heritage are increasingly taking advantage of this promising technology [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Spectral Image Processing for Museum Lighting Using CIE LED Illuminants

Martínez-Domingo

Melgosa

Okajima

et al. 2019

Sensors

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This work presents a spectral color-imaging procedure for the detailed colorimetric study of real artworks under arbitrary illuminants. The results demonstrate this approach to be a powerful tool for art and heritage professionals when deciding which illumination to use in museums, or which conservation or restoration techniques best maintain the color appearance of the original piece under any illuminant. Spectral imaging technology overcomes the limitations of common area-based point-measurement devices such as spectrophotometers, allowing a local study either pixelwise or by selected areas. To our knowledge, this is the first study available that uses the proposed CIE (Commission Internationale de l’Éclairage) light-emitting diode (LED) illuminants in the context of art and heritage science, comparing them with the three main CIE illuminants A, D50, and D65. For this, the corresponding colors under D65 have been calculated using a chromatic adaptation transform analogous to the one in CIECAM02. For the sample studied, the CIE LED illuminants with the lowest average CIEDE2000 color differences from the standard CIE illuminants are LED-V1 for A and LED-V2 for D50 and D65, with 1.23, 1.07, and 1.57 units, respectively. The work studied is a Moorish epigraphic frieze of plasterwork with a tiled skirting from the Nasrid period (12th–15th centuries) exhibited in the Museum of the Alhambra (Granada, Spain).

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Design and validation of tailored colour reference charts for monitoring cultural heritage degradation

et al. 2021

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Colour changes of cultural heritage objects can be related with degradation of materials, thus a proper colour monitoring system can be used to detect conservation problems. With this purpose, a monitoring methodology for cultural heritage preventive conservation based on tailored colour reference charts and image analysis is proposed.Reference colour charts have been designed and tested for use in museums. Charts containing 64 colour patches have been printed using high-stability inks on 4 different substrates: Acid-free paper SkyLight, Acid-free paper covered with a propylene film, FOREX® and GlassPack. The stability has been studied by accelerated ageing in an UV chamber, and the harmlessness of the materials by Oddy Test. The final selection of material, laminated paper, is a balance between the colour change upon ageing and the performance in the Oddy Test. Using this material and the proposed design, colour change of copper and silver coupons has been assessed using images that are adjusted and calibrated by an adaptive calibration framework employing a given set of reference colours which homogenises the visual information in the supplied images. Thus, regardless of the camera of origin, any processed picture will deliver reliable information of the state of the colour in the metal surfaces at the moment it was taken.Results demonstrate the adequacy of the approach and the design for colour calibration, so these charts can be used to monitor colour change of sensitive materials –metal coupons– using photographs. As colour change of reference metals is a consequence of corrosion by environmental factors this may be used as a measure of air quality in museum environments. This methodology can be used to design a low-cost preventive conservation tool, where colour change of metal coupons –or other reference materials– can be followed through image analysis of pictures taken periodically by conservators or visitors, introducing citizen science in the conservation strategy.

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Spectral information to get beyond color in the analysis of water-soluble varnish degradation

Cited by 4 publications

References 16 publications

Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

Spectral Reflectance Reconstruction Using Fuzzy Logic System Training: Color Science Application

Spectral Image Processing for Museum Lighting Using CIE LED Illuminants

Design and validation of tailored colour reference charts for monitoring cultural heritage degradation

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