- Research article
- Open Access
Identification of pigments by multispectral imaging; a flowchart method
© Cosentino; licensee Chemistry Central Ltd. 2014
- Received: 30 July 2013
- Accepted: 6 March 2014
- Published: 17 March 2014
The literature on the application of Multispectral and Hyperspectral imaging for identification of pigments on artworks is sparse. While these methods do not provide the analytical capability that spectroscopies do offer, the use of spectral imaging has the advantage of being a rapid and relatively low-cost solution for the examination of large areas. This paper presents a flowchart for the identification of historical pigments applied with gum Arabic using multispectral imaging (wavelength ranging from 360 to 1700 nm) performed with a modified digital camera for infrared, visible and ultraviolet photography; and an InGaAs camera for infrared reflectography. The flowchart method will be most successful on paint made of one layer of pure pigment, and it can selectively discriminate only a fraction of the 56 pigments analyzed. Though, considerably limited in its analytical capabilities, the low cost and speed of the workflow make the method worthwhile, even if only to localize retouching and areas appearing the same hue but painted with different pigments. The InGaAs camera is the only expensive instrument used in this study but its cost is relatively affordable for the average painting conservation studio since only a model with a low pixel count is required (320×256 pixels) rather than a more sophisticated InGaAs scanner system.
- Prussian Blue
- Multispectral Imaging
- Infrared Fluorescence
- Zinc White
- Pigment Identification
Multispectral imaging (MSI) [1, 2] and Hyperspectral Imaging [3–6], have been suggested as methods for the non-destructive identification of pigments. Though, it is mandatory to point out that these methods are problematic and the user may be subjected to draw conclusions that remain uncertain, essentially, because pigments are often mixed and overlapped in layers to make the desired color and effect.
To identify pigments with an acceptable degree of certainty, at least one other material specific technique must be used to complement hyper or multispectral imaging diagnostics. The use of MSI to tentatively identify pigments has an important advantage justifying its application: the rapid and low-cost survey of large areas. The intention of this paper is to show that with a flowchart based methodology it is possible to tentatively identify some historical pigments by means of MSI performed with simplified equipment and without the aid of imaging analysis software. This method doesn’t claim to allow the identification of all different pigments, but it will work for those which present peculiar behaviors in the range of the electromagnetic spectrum readily observable with an IR-VIS–UV modified digital camera (360–1100 nm) and an InGaAs camera (900–1700 nm). In this way, selected pigments are likely to be identified by means of MSI examination. This simplified approach, though demonstrated to be limited in its analytical diagnostic capabilities, has the benefit of being accessible and easy to implement by professionals in the art conservation and examination field.
This method is more likely to succeed when applied on artworks where pigments have been applied in one single layer and not mixed; as is the case with miniatures [6, 7], drawings  and prints. Unlike other references, which suggest the use of software algorithms to analyze the MSI images, this paper proposes a more straightforward method simply based on visual examination and the use of a photo-editing software for the characterization of features apparent in the image.
There are a number of studies on the application of each of the above mentioned imaging methods specifically for the identification of pigments: UV Fluorescence (UVF) [9–12], UV Reflected (UVR) , Infrared False Color (IRFC) [14, 15], Infrared Fluorescence [16–18] and Infrared Reflectography . Though, there is no comparative study carried out using all of those methods, and therefore this paper intends to fill that void.
The MSI images presented in this paper were acquired with a Nikon D800 DSLR (36 MP, CMOS sensor) digital camera modified for “full spectrum”, ultraviolet–visible‒infrared photography (between about 360 and 1100 nm). The CMOS sensor responds both to the near infrared and near ultraviolet ranges of the spectrum, however manufacturers install an IR cut-off filter in front of the sensor to reduce infrared transmission. There are companies that will remove this filter in commercial cameras for a small fee, and then the camera is said to be “full spectrum”. The camera is tethered to a computer to allow sharp focusing in non‒visible modes (IR and UV) using live view mode. The MSI images created with this camera do not precisely image the same area in each waveband because it is necessary to refocus the lens at the different wavelengths. In order to allow a comparative examination through the different spectral ranges, those images are uploaded as layers of a single document file in an image editing software, such as Adobe Photoshop or GIMP, and manually resized to overlap one another. Infrared Reflectography (IRR) was performed with an InGaAs camera (320×256 pixels) Merlin NIR by Indigo Systems. Some suggested references on art documentation and examination using each spectral band and the relative instrumentation for Infrared [1, 2, 20–23] and Ultraviolet [24, 25] are given.
The filters chosen for use in this paper are commercially distributed for photography and so they are easy to find. Their transmission spectra are available on the manufacturers’ websites, Schneider Optics for the B + W filters, Maxmax.com for the X-Nite filter and Heliopan for the infrared filter. This is the filter set used for the MSI: a) For Ultraviolet Reflected (UVR) photography, the B + W 403 filter is used together with the X-NiteCC1. B + W 403 allows just the UV light to pass, and X-NiteCC1 is necessary to stop the IR produced from the UV lamp; b) For Visible (VIS) photography, just the X-NiteCC1 filter is sufficient; c) For UV Fluorescence (UVF) photography, the B + W 420 must be mounted to stop the reflected UV, and the X-NiteCC1 is also necessary to exclude any infrared from the UV lamp; d) For Infrared (IR), Infrared Fluorescence (IRF) and Infrared Reflectography, just the Heliopan RG1000 is used.
A Nikon Nikkor 50 mm f/1.8D AF lens was used for all the MSI photos on the pigment swatches. Standard photography lenses are generally fine for MSI. Indeed, they are transparent from 350 nm to 1700 nm. Though, it is recommended to test the lenses for hot spots in the infrared imaging. Hot spots can be caused by a number of factors, such as coatings and/or the interaction between elements within the lens and the image sensor. Lists of other lenses tested for hot spots are available online . It is also recommended to use fixed focal lenses and avoid complex lenses that are likely to give flares in the infrared and ultraviolet photography. Also it is recommended to avoid telephoto lenses over 200 mm for MSI photography, so that the lens will be fast enough to work with the low intensity emission produced in the UV Fluorescence and IR Fluorescence imaging.
Halogen lamps are used for VIS and IR photography. For UV photography (UVF and UVR) high-Flux 365 nm LED lamps are recommended. The advantages of UV LED lighting are obvious: instant start up, no heating up, very lightweight and sturdy. These LEDs are filtered to cut off any visible light with a UV-pass glass analogous to the B + W 403. This paper considers the UV Fluorescence excited by a 254 nm UV lamp (UVF254) as an additional and separate imaging method. These lamps must be used with extreme care since this UV range (UVC) is dangerous for the eyes and skin. Infrared fluorescence (IRF) requires illumination in the visible range only, which can be implemented with a white light LED lamp filtered with the X-Nite CC1 filter to cut off emission in the near-IR.
List of pigments with the Kremer Pigments product code
Cobalt violet, 45800
Ivory black, 12000
Vine black, 47000
Burnt Sienna, 40430
Cadmium red, 21120
Cadmium yellow, 21010
Bone black, 47100
Burnt umber, 47010
Red lead, 42500
Cobalt yellow, 43500
Lamp black, 47250
Van Dyke brown 41000
Read ochre, 11574
Lead Tin yellow I, 10100
Raw Sienna, 17050
Lead Tin yellow II, 10120
Raw umber, 40610
Madder lake, 372051
Blue bice, 10184
Lac dye, 36020
Naples yellow, 10130
Cobalt blue, 45730
Cadmium green, 44510
Carmine lake, 42100
Egyptian blue, 10060
Chrome green, 44200
Cobalt green, 44200
Yellow ochre, 40010
Maya blue, 36007
Green earth, 11000
Lead white, 46000
Yellow Lake reseda, 36262
Prussian blue, 45202
Zinc white, 46300
Phthalo green, 23000
Ultramarine nat, 10510
Titanium white, 46200
Phthalo blue, 23050
All the pigments are distributed by Kremer Pigments and their relative information about composition and manufacturing can be found on the Kremer website  searching for the specified product code. The high resolution multispectral images of the pigment swatches can be accessed online  and browsed on an IIPImage  server system that allows the user to blend between the multispectral images for immediate comparison.
1st step. VIS
The logic of this flowchart is to start with the most straightforward imaging methods and move toward the less specific ones. Rectangular shapes list the pigments showing the same feature such as, for example, a red UV fluorescence. If the same group of pigments shows also other properties in common, these are listed in the bottom of the same rectangular shape. The first step is to assign the pigment to one of these color categories: white, black, blue, green, yellow, brown, red. The flowchart is likely to succeed for the identification of paints made of just one pure pigment. If the paint is a mixture or a glaze, multispectral imaging loses its identification capacity. In that case, it’s recommended to first perform an examination under magnification, with at least a hand-held USB microscope, to check if the paint is a mixture. Particular attention should be directed towards greens and violets. Indeed, often they are a mix of blue and yellow for the green, and red and blue for the violet. They could also be a layered glaze, yellow over blue for the greens and red over blue for the violets.
2nd step. UVR
3rd step. UVF
As described for the UVR imaging, UV fluorescence comes just from the surface of the paint layer and it isn’t influenced by layers underneath. Though in this case, the varnish does play a major role since it generally exhibits strong fluorescence and could overwhelm the actual fluorescence of the pigments. Consequently, MSI documentation is recommended when the varnish is removed from the artwork. These decision categories are defined for the UV fluorescence: none (meaning no sizeable fluorescence is observed, i.e. RGB < 30), white, blue, red, orange, yellow.
4th step. UVF 254
A 254 nm UV lamp allows the observation of fluorescence otherwise not excited by the 365 nm UV lamp discussed in the 3rd step, such as that which particularly occurs with madder lake. The same decision steps as for UVF are defined: none (meaning no sizeable fluorescence is observed), red, orange, yellow, white. Again, as for the UVF, these color categories are to be intended liberally since the perception of the color is not well defined.
5th step. IRF
Only a few pigments exhibit Infrared Fluorescence, namely cadmium based pigments and Egyptian blue, making it a highly specific method. Just two decision steps: yes (RGB > 10), or none.
6th step. IR
7th step. IRR
8th step. IRFC
For the last step comes Infrared false color. As we saw in Figure 6, the infrared false color appearance is strongly influenced by the under layer, and as for the IR step this method is useful only for single layer paint examination. The categories are defined for the color produced as: red, pink, green, black, white, and purple.
The four most used carbon-based blacks were tested and, as expected, none of the imaging methods can distinguish among them.
Five brown pigments were tested. As expected, none of the imaging methods can distinguish among them.
A case study
This paper represents the first attempt to correlate MSI methods to achieve a preliminary pigment identification. This study focused on pigments applied with gum Arabic, which is the medium used most in watercolor, a technique where pigments are less likely to be blended and overlapped. Further work is necessary to take into account the effects of other mediums, linseed oil, tempera and acrylic, and degree of aging.
It was shown that some particularly useful features such as UV Fluorescence, IR Fluorescence and the losses of infrared reflectance in the IRR imaging allow for rather reliable identification of certain pigments. On the other hand this MSI flowchart should be seen as complementary to analytical methods, in particular, elemental spectroscopies, such as X-ray Fluorescence spectroscopy. For example, on the blue pigments flowchart it is showed that Prussian blue and azurite are just distinguishable by their IRFC, which is the less reliable discriminant. Though, XRF can easily distinguish among them through the presence or absence of significant copper content.
Unfortunately, it is not always possible to perform all the 8 imaging methods to study an artwork. This is the case of paintings with the old varnish whose UVF can overwhelm that of the pigments, and the case where it is not possible to have total darkness to correctly execute IRF and UVF. In these cases, the flowchart can be still followed bypassing the missing steps, but losing, of course, part of its identification capability.
It would be valuable to compare this flowchart approach with other spectral imaging technologies [36, 37], methods which are currently investigated and which use estimation techniques for visible spectrum imaging , and could become more powerful with the implementation of liquid-crystal tunable filters or interference filters. It would be also worth to apply the flowchart approach to other conservation studies on which Hyperspectral Imaging has proven successful such as on inks [39, 40] and parchment .
This work has been possible thanks to Kremer Pigments who has provided the pigment samples. Thanks also to the Ingels Collection, Sweden for permitting the use of the material on the Madonna and Child panel.
- Cosentino A: A practical guide to panoramic multispectral imaging. e-Conservation Magazine. 2013, 25: 64-73.Google Scholar
- Frey FS, Warda J, American Institute for Conservation of Historic and Artistic Works, Digital Photographic Documentation Task Force: The AIC guide to digital photography and conservation documentation. 2008, Washington, D.C: American Institute for Conservation of Historic and Artistic WorksGoogle Scholar
- Zhao Y, Berns RS, Taplin LA, Coddington J: An investigation of multispectral imaging for the mapping of pigments in paintings. Proc. SPIE 6810. 2008, San Jose, CA: Computer Image Analysis in the Study of ArtGoogle Scholar
- Kubik M: Chapter 5 hyperspectral imaging: a new technique for the non-invasive study of artworks. Physical Techniques in the Study of Art, Archaeology and Cultural Heritage, volume 2. 2007, Oxford, UK: Elsevier, 199-259.View ArticleGoogle Scholar
- Padoan R, Steemers T, Klein M, Aalderink B, de Bruin G: Quantitative hyperspectral imaging of historic documents. 9th International Conference on NDT of Art. 2008, Jerusalem, Israel:Google Scholar
- Isacco E, Darrah J: The ultraviolet-infrared method of analysis, a scientific approach to the study of Indian miniatures. Artibus Asiae. 1993, 53 (3/4): 470-491. 10.2307/3250528.View ArticleGoogle Scholar
- Melessanaki K, Papadakis V, Balas C, Anglos D: Laser induced breakdown spectroscopy and hyper-spectral imaging analysis of pigments on an illuminated manuscript. Spectrochim Acta B At Spectrosc. 2001, 56: 2337-2346. 10.1016/S0584-8547(01)00302-0.View ArticleGoogle Scholar
- Havermans J, Aziz HA, Scholten H: Non destructive detection of iron-gall inks by means of multispectral imaging. Restaurator. 2003, 24: 88-94.Google Scholar
- Buzit Tragni C: Advanced residency program in photograph conservation, Image Permanence Institute, Rochester Institute of Technology. The use of ultraviolet-induced visible fluorescence for examination of photographs. 2005, http://notesonphotographs.org/images/d/df/Claire_Tragni_for_web.pdf,Google Scholar
- René de la Rie E: Fluorescence of paint and varnish layers (part I). Stud Conserv. 1982, 27 (1): 1-7. 10.2307/1505977.View ArticleGoogle Scholar
- René de la Rie E: Fluorescence of paint and varnish layers (part III). Stud Conserv. 1982, 27 (3): 102-108.View ArticleGoogle Scholar
- Comelli D, Valentini G, Nevin A, Farina A, Toniolo L, Cubeddu R: A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces. Rev Sci Instrum. 2008, 79: 086112-10.1063/1.2969257.View ArticleGoogle Scholar
- Aldrovandi A, Buzzegoli E, Keller A, Kunzelman D: Investigation of painted surfaces with a reflected UV false color technique. 2005, Italy: art’05, 8th International Conference on Non Destructive Investigations and Micronalysis for the Diagnostics and Conservation of the Cultural and Environmental Heritage LecceGoogle Scholar
- Moon T, Schilling MR, Thirkettle S: A note on the use of false-color infrared photography in conservation. Stud Conserv. 1992, 37 (1): 42-52.View ArticleGoogle Scholar
- Hoeniger C: The identification of blue pigments in early Sienese paintings by color infrared photography. J Am Inst Conserv. 1991, 30 (2): 115-124. 10.1179/019713691806066782.View ArticleGoogle Scholar
- Bridgman CF, Gibson HL: Infrared luminescence in the photographic examination of paintings and other art objects. Stud Conserv. 1963, 8 (3): 77-83.View ArticleGoogle Scholar
- Accorsi G, Verri G, Bolognesi M, Armaroli N, Clementi C, Miliani C, Romani A: The exceptional near-infrared luminescence properties of cuprorivaite (Egyptian blue). Chem Commun. 2009, 23: 3392-3394.View ArticleGoogle Scholar
- Thoury M, Delaney JK, De la Rie ER, Palmer M, Morales K, Krueger J: Near-infrared luminescence of cadmium pigments: in situ identification and mapping in paintings. Appl Spectrosc. 2011, 65 (8): 939-951. 10.1366/11-06230.View ArticleGoogle Scholar
- Gargano M, Ludwig N, Poldi G: A new methodology for comparing IR reflectographic systems. Infrared Phys Technol. 2007, 49: 249-253. 10.1016/j.infrared.2006.06.013.View ArticleGoogle Scholar
- Mairinger F: The infrared examination of paintings. Radiation in Art and archeometry. Edited by: Creagh DC, Bradley DA. 2000, : Elsevier, 40-55.View ArticleGoogle Scholar
- Mayer JW: Infrared reflectography and hiding thickness. The Science of Paintings. 2000, New York: Springer-Verlag, 125-127.Google Scholar
- van Asperen JRJ, Boer d: Reflectography of paintings using an infrared vidicon television system. Stud Conserv. 1969, 14 (3): 96-118.View ArticleGoogle Scholar
- Falco CM: High-resolution infrared imaging. 2010, San Diego: SPIE Optics+Photonics ConferenceView ArticleGoogle Scholar
- Savage G: Forgeries, fakes, and reproductions, a handbook for collectors. 1976, London: White Lion Publishers Ltd, 3Google Scholar
- Rorimer JJ: Ultraviolet rays and their use in the examination of works of art. 1931, New York: Metropolitan Museum of Art, 1Google Scholar
- Hannemyr G, IR L: What lenses are suitable for IR photography. DPanswers.com http://dpanswers.com/content/irphoto_lenses.php
- AIC PhotoDocumentation Targets (AIC PhD Targets), conservation‒us.org. http://www.rmimaging.com/aic_phd.html,
- Kremer Pigments Inc: Kremer Pigments Inc. http://kremerpigments.com/,
- Cultural Heritage Science Open Source”. Blog. References/Pigments page http://chsopensource.org/multispectral-imaging-pigments/
- IIPImage server system. http://iipimage.sourceforge.net/,
- Lawrence Berkeley National Laboratory Pigment Database. http://coolcolors.lbl.gov/LBNL-Pigment-Database/database.html,
- Kirby J, Spring M, Higgit C: The technology of eighteenth and nineteenth century Red lake pigments. National Gallery Tech Bull. 2007, 28: 69-95.Google Scholar
- Kirby J, Spring M, Higgit C: The technology of Red lake pigment manufacture: study of the dyestuff substrate. National Gallery Tech Bull. 2005, 26: 71-87.Google Scholar
- FitzHugh EW: Artists’ Pigments: A Handbook of Their History and Characteristics. 1997, Washington, DC: National Gallery of ArtGoogle Scholar
- Art Institute Chicago: UV Image: Madder lake pigment revealed. http://www.artic.edu/aic/resources/resource/572,
- Fischer C, Kakoulli I: Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications. Stud Conserv. 2006, 14 (Supplement 1): 3-16(14).View ArticleGoogle Scholar
- Casini A, Lotti F, Baronti S, Castagna P, Stefani L: An image spectroscopy system for the analysis and documentation of paintings. Sci Tech Cult Herit. 1992, 1: 33-43.Google Scholar
- Berns RS, Imai FH: The use of multi-channel visible spectrum imaging for pigment identification. 2002, Rio De Janeiro Preprints: ICOM Committee for Conservation, 13th triennial meetingGoogle Scholar
- Tse S, Goltz D, Guild S, Orlandini V, Trojan-bedynski M, Richardson M: Effect of aqueous treatments on nineteenth-century iron-gall-Ink documents: assessment using hyperspectral imaging. Book Paper Group Ann. 2009, 28: 75-Google Scholar
- Havermans J, Aziz HA, Scholten H: Non destructive detection of iron-gall inks by means of multispectral imaging part 2: application on original objects affected with iron-gall-Ink corrosion. Restaurator. 2008, 24 (2): 88-94.Google Scholar
- Giacometti A, Campagnolo A, MacDonald L, Mahony S, Terras M, Robson S, Weyrich T, Gibson A: Cultural Heritage Destruction: Documenting Parchment Degradation via Multispectral Imaging. 2012, London: Electronic Visualisation and the Arts (EVA)Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.