“IRIS”; a novel spectral imaging system for the analysis of Cultural

Heritage objects

V. Papadakis*, Y. Orphanos, S. Kogou, K. Melessanaki, P. Pouli, C. Fotakis

Foundation for Research and Technology - Hellas, Institute for Electronic Structure and Laser

*email: billyp@iesl.forth.gr

ABSTRACT

A new portable spectral imaging system is herein presented capable of acquiring images of high resolution (2MPixels)

ranging from 380 nm up to 950 nm. The system consists of a digital color CCD camera, 15 interference filters covering

all the sensitivity range of the detector and a robust filter changing system. The acquisition software has been developed

in “LabView” programming language allowing easy handling and modification by end-users. The system has been tested

and evaluated on a series of objects of Cultural Heritage (CH) value including paintings, encrusted stonework, ceramics

etc. This paper aims to present the system, as well as, its application and advantages in the analysis of artworks with

emphasis on the detailed compositional and structural information of layered surfaces based on reflection & fluorescence

spectroscopy. Specific examples will be presented and discussed on the basis of system improvements.

Keywords: Spectral imaging, diagnosis, Cultural Heritage

1. INTRODUCTION

Spectral imaging is a well-known methodology for the analysis of paintings with high spatial resolution [1]. Through the

years a number of systems have been developed to fully exploit the advantages offered by this technique in mapping the

compositional and stratigraphic information of the analysed surfaces [2]. The design of these instruments is based on two

different principles of operation. In the first one the white light reflected by the object is analyzed by imaging

monochromators resulting into images of high spatial but limited spectral information [3-17]. Their advantages is that

they can be operated under any lighting conditions and thus allow for field measurements. The second one is based on

the illumination of the object by monochromatic light providing high spatial as also spectral information [18, 19]. Its

main disadvantages are the limited scanning speed, as well as, the restriction for limited environmental lighting upon

operation. In-house or laboratory measurements can be performed with both techniques, since the environmental light

conditions are easily controlled. On the contrary field measurements using ambient day light promote imaging

monochromators as the only choice. Analytical problems requiring the application of both techniques simultaneously do

exist and are based on the fluorescence spectral imaging [20-22]. In this case, researchers need to control the illumination

wavelength for excitation as also to record the full fluorescence spectrum with high spatial resolution.

In this work we are presenting an imaging monochromator, with emphasis on portability and robust structure to enable

reliable field measurements, which also allows for high spatial and spectral resolution. The system IRIS [23]

incorporates a high resolution CCD sensor (2 MPixels) along with a spectral resolution of 15 band-pass filters, ranging

from UV (380 nm) up to NIR (950 nm). The system is mobile, very robust, sensitive and easy to be controlled by the

end-users. The operating software is tailor made and has been developed in LabView (National Instruments)

programming interface, allowing users to easily handle and modify its code when necessary.

2. MATERIALS AND METHODS

2.1. Hardware design

The case-housing of IRIS has been completely developed by aluminum. The filter changing mechanism is an “umbrella”

type of filter wheel, with two ball bearings that support the rotational movement on the center of its rotational axis. The

system was designed to accept any type of C-mount objective lenses, allowing a wide range of choices.

The filter wheel incorporates 12 band-pass filters (Omega Optical) with 25nm bandwidth ranging from 400nm up to

950nm with a step of 50nm, a UV filter (low pass 400nm), one infrared filter (high pass 700nm) and last one visible filter

(400nm-700nm). All filters are custom made so that each filter is selectively thinned to provide achromaticity to the

system, enabling same focal point for each wavelength.

O3A: Optics for Arts, Architecture, and Archaeology III, edited by Luca Pezzati, Renzo Salimbeni, Proc. of SPIE Vol. 8084, 80840W · © 2011 SPIE · CCC code: 0277-786X/11/$18 · doi: 10.1117/12.889510

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The movement is controlled by a step motor (), its driver () and a DAQ card (USB-6008, National Instruments) that

interfaces with the computer.

The detector is based on a color CCD sensor with 2MPixel spatial resolution (Unibrain Fire-I 702c), interfacing with the

PC under the IEEE1394a Fire-wire protocol.

2.2. Software design

All software is developed in LabView (National Instruments) programming interface. Following the design architecture

is described:

Most of the user interface (UI) is occupied by a large image frame to enhance the visibility of spatial image detail. Under

the same window, the user has the option to control the position of the filter wheel, the camera shutter value, while

recording of any requested monochromatic image on computers’ HDD is possible. Additionally, the software displays a

histogram of the intensity values of each frame, providing users with a method to fully exploit the dynamic range,

without saturating the sensor.

The systems filter wheel is controlled via the DAQ card from National Instruments enabling the use of NI-DAQmx

software toolbox. The camera is compatible with the LabView interface and all algorithms for control and processing

have been developed under the (NI-Vision Development Module). Camera acquisition, as also sensor parameters like

shutter, gain and white balance are enabled for calibration purposes. Since the camera sensor is color, via Bayer filters on

the CCD, the system has been pre-calibrated to detect light from specific color planes, based on the interference filter

selected.

The processing of the acquired data (spectral images) is realized through three individual programs. In the first program

calibration of the system is completed, through background correction and subtraction methods. More specifically, in

each spectral image the algorithm initially subtracts the dark-noise-image while normalization is achieved by background

correction via the reference card images. This calibration methodology is described in the following section. The second

program is used for spatial registration purposes of the multiple spectral images recorded. In this way the user can correct

possible displacement of the field-of-view due to fine focusing adjustments required for every wavelength. The

technique is based on a basic pattern recognition algorithm, where the user has to select a major feature on an image.

During this procedure, the software automatically detects the selected feature in every image and shifts it to the correct

position. Lastly, processing is completed by an algorithm (spectrum from pixel) that can manage the total of the

calibrated images (spectral cube) enabling the extraction of a full reflectance spectrum from any selected pixel or region

of the image. Additionally, the user has the option to save the spectrum in text format for further processing.

Figure 1: screenshot of the “spectrum from pixel” software displaying the extraction of the reflectance spectrum from a

selected area of the red pigment (green circle) developed in LabView. In the left hand side of the studied image the

reference paint pallet is seen.

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2.3. Calibration

Before each measurement the system has to be calibrated in order to achieve the “white calibration line”, based on the

alternate light conditions and the objective lenses used. For this reason a white reflective reference card made of regular

Lithopone (ZnS 30%, BaSO4 70%) has been manufactured in our labs and used before each measurement. This aims for

two different calibration purposes; one to calibrate intensity under the different wavelengths, while the second aims to

correct possible spatially illumination variations. After acquiring calibration images in every wavelength, the system is

ready to record the spectral image. Following acquisition, images are then corrected by the reference card data resulting

to a spectrally and spatially correct spectral cube.

Elimination of the dark noise, potentially existing due to long exposure times, is also possible. To achieve this, a black-

image is acquired, simply by closing the iris of the objective lens, and the constant image of the thermal electrons is

recorded. Calibration is then achieved by subtracting the black-image from the recorded data.

3. APPLICATIONS

The system has been evaluated on a series of objects of CH value. In the current communication specific examples of

these studies are discussed and presented with the aim to exploit the potential of the system.

3.1. Pigment analysis

The system’s ability to provide reliable results with high resolution in the compositional analysis of painting materials

was systematically tested on model and real paintings. An example is herein discussed to show the analytical procedure

for the identification of an unknown red pigment on a tempera painting by comparing its reflectance spectra to the ones

recorded for a series of reference paints on a pallet. The reference paint pallet was prepared for calibration purposes and

contains a series of commonly used pigments dispersed in Arabic gum applied on parchment. The red pigments that were

included in the pallet and studied in our case are: vermillion (HgS), Mars-Red (Fe2O3 (Al2O3)) and Cadmium red

(CdSxSe(1-x)). The painting, of unknown artist, is made of tempera paints on a prepared wooden panel and presents a rural

landscape with houses. The example described herein refers to the identification and chemical analysis of the red

pigment shown on the chimney of the left house of the painting, using the IRIS system.

The reflectance spectra from the reference pigment pallet are studied. Figure 2 shows the intensity measurement of a red

area (red 7, green circle in image 1) in comparison to the three reference red pigments of the pallet.

Figure 2. Reflectance spectra of a selected red area, in comparison to the reference red samples, as extracted from the

spectral images measured.

The investigated red pigment (red7) in graph shows similar behavior to the recorded Vermilion reference spectrum.

Specifically the graph follows the same behavior to the Vermilion one through most the studied range of wavelengths,

while differences in the intensity are recorded below 450nm and above 650nm. In the case of longer wavelengths, the

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difference is due to the fact that in the reference samples the employed pigments are pure, of relatively high thickness

while a layer of white preparation exists which enhances the final colour. Furthermore, other reasons for the observed

differences may be the contribution to the final spectrum from the other pigments that are mixed with, or they lay under,

the studied one. On the other hand the differences observed below 450nm are most probably due to the existence of a

varnish layer. Commonly found on artworks, varnishes tend to absorb strongly in the shorter wavelengths with their

absorbance behavior closely related to the physicochemical properties, the thickness and the age of the varnish layer.

3.2. Monitoring of cleaning interventions

Furthermore the system’s potential to evaluate and monitor the cleaning process, while providing information on the

state and morphology of the cleaned surface, has been proven through series of tests on encrusted stonework [4]. In the

example discussed here the system has been tested as a monitoring tool to the laser assisted removal of pollution crust

from marble. The principle of operation relies on the differential penetration of monochromatic light in matter, which

allows mapping of the progress and the depth of cleaning in real time by calculating the differences of images recorded

at two spectral bands (in our case at 450 nm and 950 nm). Necessary limitation to ensure the applicability of this

methodology is the existence of an appreciable difference in reflectivity between the stone and the encrustation

materials, at least in one of the two wavelengths.

Figure 3 shows a white pentelic marble fragment covered with a relatively thin and homogeneous crust of dark brown

colour. Such encrustations are formed due to the exposure of the object to environmental conditions and apart from

disfiguring they also pose the life and longevity of the object itself into danger. Among the cleaning methodologies that

have been introduced to face these problems, lasers are considered the most safe, controlled and straight-forward ones

mainly due to their self-limiting nature. More specifically the use of the fundamental wavelength of a Q-switched

Nd:YAG laser system at 1064 nm at fluence values just above the ablation threshold [24, 25] was found to remove these

types of crust effectively and reliably.

The IRIS imaging system was employed to record the intensity of the reflected light at different spectral bands for

successive laser cleaning pulses. It was noticed that a significant difference in the slopes of the reflectance curves of 450

nm and 950 nm exists, which allows to get information on the thickness of the remaining encrustation during the

cleaning process. The maximum contrast was achieved when the 950 and 450nm spectral images were divided and

following this observation the optimum laser irradiation conditions to ensure a safe cleaning intervention can be

established. Real time monitoring of the cleaning level can be achieved by processing the spectral images of certain

snapshots of the cleaning to get an intensity ratio map (IRM) and then compare the irradiated areas to reference ones.

Figure 3a shows the IRM image taken in one of our tests in comparison to the corresponding visible one, after three

successive pulses. As it can be seen from the following graph pulse number three is the threshold for an optimum

cleaning while above the fifth pulse over-cleaning and potential damage of the marble surface are likely to occur.

a) b) Figure 3.a) Visible (left) and intensity ratio I950/I450 (right) images of the tested marble surface showing cleaning monitoring,

b) the reflectance ratio (I950 nm/ I450 nm) recorded upon irradiation (1064 nm, F = 0.5 J cm−2) of a marble surface with

pollution crust versus successive laser pulses.

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4. CONCLUSIONS

The system was shown to successfully acquire measurements with high spatial and spectral resolution. Measurements are

consistent and repetitive, based on a simple calibration procedure. Evaluation of the system was achieved in many

applications. Discrimination of pigments in artworks was succeeded in both high spectral and spatial resolution on the

basis of direct comparison to a reference paint pallet of known composition. Laser cleaning intervention of encrusted

stonework was monitored in real time reliably, on the basis of measuring the remaining encrustation’s thickness.

IRIS system is proven to be a consistent, sensitive and delicate tool for material characterization on CH surfaces while its

ability to monitor cleaning interventions on line was shown.

5. ACKNOWLEDGMENTS

This work has received funding from the EC FP7 project “LASERLAB-EUROPE”, grant agreement n° 228334.

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