Andrea Casini

Principal component analysis of visible and near-infrared multispectral images of works of art

Abstract Principal component analysis (PCA) was applied to a very simple case of a tempera panel painted with four known pigments (cinnabar, malachite, yellow ochre and chromium oxide). The four pigments were spread pure as well as dilute with carbon black (5% w/w, 10% w/w) thus creating 12 homogeneous areas of the same size. The panel was imaged by a Vidicon camera in the visible and near-infrared regions (420–1550 nm) resulting in a set of 29 images. PCA was applied by taking various subsets of the input data. From the analysis of this simple and predictable case study some guidelines are synthesized and proposed for the application to actual work of art. Results are presented for the painted panel. Preliminary results are also reported for the Luca Signorellis “Predella della Trinita”. The multivariate image analysis results in the visible and near-infrared regions show that it is possible to use the multispectral image data in order to get a segmentation and a classification of painted zones by pigments with different chemical composition or physical properties.

Principal Component Analysis of Near-Infrared and Visible Spectra: An Application to a XIIth Century Italian Work of Art

Statistical data processing was performed on the spectra of a painting recorded in the near-infrared (near-IR) and visible (Vis) region by a totally nondestructive method. Results are discussed also in connection with colorimetric analysis.

Hyper-Spectral Acquisition on Historically Accurate Reconstructions of Red Organic Lakes

Our cultural heritage is constituted by irreplaceable artworks that must be known and preserved. Their study and documentation should be in principle carried out using non-invasive approaches. The technological advances in spectroscopic imaging acquisition devices made it possible to apply this methodology to such purpose. In this context, the present paper discusses a particularly challenging task within the conservation field, which is the identification of red lake pigments in artworks, applying Vis-NIR hyper-spectral imaging spectroscopy. The latter was used to characterize and discriminate between historically accurate paint reconstructions of brazilwood (vegetal) and cochineal (animal) lake pigments. The same paints were also analyzed with Fiber Optic Reflectance Spectroscopy to validate the data obtained with the imaging method. The requirements for a successful identification of these pigments are addressed, and future research is suggested in order to increase the usefulness of the technique’s application.

Extending hyperspectral imaging from Vis to NIR spectral regions: a novel scanner for the in-depth analysis of polychrome surfaces

In recent years Hyper-Spectral Imaging (HSI) technologies have become well-established for applications in the field of Cultural Heritage, and in particular for non-invasive analysis and high quality documentation of paintings and other polychrome surfaces. This paper reports on the latest developments of the on-going research at IFAC-CNR, where a new prototype of a high-performance hyper-spectral scanner, operating in the NIR spectral region (900-1700nm range), was designed, assembled and tested. This new NIR scan-head was designed to be mounted on the same mechanical structure used for the earlier IFAC-CNR scanner prototype, which operated in the 400-900nm range. As ultimate goal the whole system would be intended to provide 2D hyper-spectral data on the extended 400-1700nm range, so as to strongly improve the capability of pigment discrimination, and to increase the possibility of visualizing the underlying features of the polychrome surfaces (such as under-drawings, pentimenti, etc.). In the present version, the NIR scan-head operates with a spectral sampling rate of about 2 nm, and a spatial sampling rate of about 9 dots per millimeter. The results of testing and characterization of the new high resolution NIR IFAC-CNR scanner are presented, with a focus on the main technical problems tackled in customizing the new system for the investigation and documentation of paintings.

Integrated non-invasive technologies for the diagnosis and conservation of the cultural heritage

The necessity of non-invasive measurements is stressed for studies of works of art. The integration of different techniques can supply a large quantity of information without any sampling. As a case study, Leonardo da Vincis Madonna of the Yarn Winder has been considered. The preliminary results of an investigation with fibre optic reflectance spectroscopy and hyper-spectral image spectroscopy are reported and discussed.

Fiber Optics Reflectance Spectroscopy: A Non-destructive Technique for the Analysis of Works of Art

From the results reported, the FORS device can be considered a useful and non-invasive tool for acquiring spectral information from paintings and wall-paintings in order to identify pigments, to analyze color changes, to monitor the status-of-health, and to detect the presence of alteration products.

Accuracy in Colour Reproduction: Using a ColorChecker Chart to Assess the Usefulness and Comparability of Data Acquired with Two Hyper-Spectral Systems

Hyper-spectral imaging has been applied as an in situ technique for the study and accurate digital documentation of coloured artworks. Providing spectral and colorimetric characterisation across the entire surface of an object, it can be used to identify the coloured materials, measure colour changes, and document it with high fidelity. However, depending on the system used, data accuracy and reliability may vary. In this work, developed within the Round Robin Test being carried out by COSCH Working Group 1, an X-Rite® ColorChecker Classic chart was analysed with two push-broom hyper-spectral systems developed by different groups (IFAC-CNR and IP-UEF), in the 400-1000 nm range, and the data obtained were compared. This comparison allowed to assess the accuracy of colour reproduction processes performed by the two systems. The results obtained are satisfactory in terms of spectral and colorimetric accuracy for some colours, but show differences at both ends of the visible range.

Quality issues for archival of ancient documents

This paper reports about a study concerning the application of error bounded encoding to lossy image compression of ancient documents handwritten on parchments. Images are acquired in the RGB color space and previously transformed in the YUV color coordinate system before coding. The coding algorithm, named RLP, considered here is based on a classified DPCM enhanced by a fuzzy clustering initialization and followed by context based statistical modeling and arithmetic coding of prediction residuals that are quantized with user defined odd step sizes to allow rate control with a minimum peak error over the whole image, so as to exactly limit local distortions. Each YUV component is coded separately; after decoding images are transformed back to RGB color space and compared with the originals in order to quantify distortions. A relationship bounding the peak errors in the RGB color space one the peak error is fixed in the YUV color space is derived. An algorithm originally designed for estimating signal-dependent noise parameters and used to obtain useful information about the images of the documents is also reported in the paper. The performances of the coding method are superior with respect to conventional DPCM schemes thanks to its flexibility and robustness to changes in type of images. For the compression ratios requested by this application the gain of RLP over JPEG is consistent: nearly 2 dB and 5 dB in PSNR for compression ratios of 10 and 5 respectively.

Imaging Spectroscopy for the Non-invasive Investigation of Paintings

This chapter describes a portable apparatus for the non-invasive examination of paintings based on a lead sulphide vidicon camera that works in the 400–2000 nm range. Imaging spectroscopy is achieved by collecting a multi-wavelength sequence of near-monochromatic images in the investigated area. After amplitude normalization and geometrical registration, the reflectance spectra can be reconstructed. Pigment identification may be made by comparing these spectra with those of a database of reference pigments and paintings. More detailed investigations on the pigment layers are afforded by appropriate algorithms, which supply distribution maps that can easily be correlated with the visual aspect of the painting. Examples of applications on test objects and on a XVI century Italian painting are reported. A brief review is also given of the modern infrared solid-state cameras that are most suited to replace the noisy and instable lead sulphide vidicon cameras in these applications.

Segmentation of Multispectral Images of Works of Art through Principal Component Analysis

Investigation of materials constituting painted layers of works of art (panels, canvas, frescoes) can be profitably done by means of non-destructive optical techniques based on the analysis of reflectance spectra in the visible and near infrared regions.