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Sensor Techniques for Artworks Analysis and Investigations
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Sensor Techniques for Artworks Analysis and Investigations

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (29 September 2023) | Viewed by 7661

Special Issue Editor

Dr. John K. Delaney

E-Mail Website
Guest Editor
National Gallery of Art, Washington, DC, USA
Interests: development and application of macro-scale multimodal imaging spectroscopy sensors for the study or works of art; elemental, reflectance, thermal and luminescence; elemental and molecular spectroscopy of artist materials; electro-optical systems engineering; development of exploitation software for spectral data cubes of works of art
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Edition of the journal Sensors is focused on original research involving the use of sensor techniques to study works of art and manuscripts. Specifically, we are interested in papers that address such areas as the development, application, and exploitation of data from sensors optimized for the study of art and manuscripts. The goal is to collect a diverse set of papers that span a wide range of remote sensing imaging modalities; for example, multispectral or imaging spectroscopy (reflectance, molecular, luminescence, thermal, or mid-Infrared, X-ray fluorescence, etc.) and 3D imaging (stereo photography, structured light, LIDAR, etc.) coupled with a chemical imaging modality. Papers focused on performance analysis to define or provide guidance for the construction of optimized sensors are also of interest. Areas of interest in terms of data exploitation include data fusion of imaging modalities acquired with different sensors, novel algorithms that provide material maps from the exploited data, and those that contribute to codicology studies of the artifacts themselves. The works of art of interest include polychrome objects (paintings, wall paintings, and sculptures) and works on paper (paintings, drawings, and historical texts and palimpsest).

Dr. John K. Delaney
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • reflectance imaging spectroscopy
  • mid-Infrared imaging spectroscopy
  • X-ray fluorescence imaging spectroscopy
  • hyperspectral imaging
  • image processing
  • 3D imaging
  • cultural heritage imaging
  • sensors
  • artificial intelligence
  • machine learning

Published Papers (4 papers)

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Research

14 pages, 6466 KiB  
Article
A Tailor-Made, Mirror-Based Infrared Scanner for the Reflectography of Paintings: Development, Features, and Applications
by Marco Gargano, Daniele Viganò, Tiziana Cavaleri, Francesco Cavaliere, Nicola Ludwig and Federica Pozzi
Sensors 2023, 23(9), 4322; https://doi.org/10.3390/s23094322 - 27 Apr 2023
Viewed by 1292
Abstract
Since infrared reflectography was first applied in the 1960s to visualize the underdrawings of ancient paintings, several devices and scanning techniques were successfully proposed both as prototypes and commercial instruments. In fact, because of the sensors’ small dimension, typically ranging from 0.1 to [...] Read more.
Since infrared reflectography was first applied in the 1960s to visualize the underdrawings of ancient paintings, several devices and scanning techniques were successfully proposed both as prototypes and commercial instruments. In fact, because of the sensors’ small dimension, typically ranging from 0.1 to 0.3 megapixels, scanning is always required. Point, line, and image scanners are all viable options to obtain an infrared image of the painting with adequate spatial resolution. This paper presents a newly developed, tailormade scanning system based on an InGaAs camera equipped with a catadioptric long-focus lens in a fixed position, enabling all movements to occur by means of a rotating mirror and precision step motors. Given the specific design of this system, as the mirror rotates, refocus of the lens is necessary and it is made possible by an autofocus system involving a laser distance meter and a motorized lens. The system proved to be lightweight, low cost, easily portable, and suitable for the examination of large-scale painting surfaces by providing high-resolution reflectograms. Furthermore, high-resolution images at different wavelengths can be obtained using band-pass filters. The in-situ analysis of a 16th-century panel painting is also discussed as a representative case study to demonstrate the effectiveness and reliability of the system described herein. Full article
(This article belongs to the Special Issue Sensor Techniques for Artworks Analysis and Investigations)
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14 pages, 22965 KiB  
Article
A Method for Spatially Registered Microprofilometry Combining Intensity-Height Datasets from Interferometric Sensors
by Sara Mazzocato and Claudia Daffara
Sensors 2023, 23(8), 4144; https://doi.org/10.3390/s23084144 - 20 Apr 2023
Cited by 4 | Viewed by 1072
Abstract
A recognized problem in profilometry applied to artworks is the spatial referencing of the surface topography at micrometer scale due to the lack of references in the height data with respect to the “visually readable” surface. We demonstrate a novel workflow for spatially [...] Read more.
A recognized problem in profilometry applied to artworks is the spatial referencing of the surface topography at micrometer scale due to the lack of references in the height data with respect to the “visually readable” surface. We demonstrate a novel workflow for spatially referenced microprofilometry based on conoscopic holography sensors for scanning in situ heterogeneous artworks. The method combines the raw intensity signal collected by the single-point sensor and the (interferometric) height dataset, which are mutually registered. This dual dataset provides a surface topography registered to the artwork features up to the precision that is given by the acquisition scanning system (mainly, scan step and laser spot). The advantages are: (1) the raw signal map provides additional information about materials texture, e.g., color changes or artist marks, for spatial registration and data fusion tasks; (2) and microtexture information can be reliably processed for precision diagnostic tasks, e.g., surface metrology in specific sub-domains and multi-temporal monitoring. Proof of concept is given with exemplary applications: book heritage, 3D artifacts, surface treatments. The potential of the method is clear for both quantitative surface metrology and qualitative inspection of the morphology, and it is expected to open future applications for microprofilometry in heritage science. Full article
(This article belongs to the Special Issue Sensor Techniques for Artworks Analysis and Investigations)
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18 pages, 8796 KiB  
Article
From Materials to Technique: A Complete Non-Invasive Investigation of a Group of Six Ukiyo-E Japanese Woodblock Prints of the Oriental Art Museum E. Chiossone (Genoa, Italy)
by Marco Gargano, Margherita Longoni, Valeria Pesce, Maria Chiara Palandri, Aurora Canepari, Nicola Ludwig and Silvia Bruni
Sensors 2022, 22(22), 8772; https://doi.org/10.3390/s22228772 - 13 Nov 2022
Cited by 1 | Viewed by 2549
Abstract
In the present work, a complete non-invasive scientific investigation of six Utagawa Kunisada’s woodblock prints (nishiki-e) belonging to the Oriental Art Museum “E. Chiossone” (Genoa, Italy), was performed in situ. The campaign started with high resolution multiband imaging (visible, multiband fluorescence, [...] Read more.
In the present work, a complete non-invasive scientific investigation of six Utagawa Kunisada’s woodblock prints (nishiki-e) belonging to the Oriental Art Museum “E. Chiossone” (Genoa, Italy), was performed in situ. The campaign started with high resolution multiband imaging (visible, multiband fluorescence, near infrared) followed by reflectance transformation imaging (RTI) to characterize and highlight the peculiar printing techniques and the condition of the support. Then fiber optics reflectance spectroscopy (FORS), spectrofluorimetry, Raman and reflectance Fourier-transform infrared (FTIR) spectroscopies were successfully applied in synergy for the investigation of the printing materials (pigments, binders, support). The results obtained represent a set of very important information for these never-before-studied works of art, useful to the different professionals involved: historians, conservators and curators. The materials identified were completely in agreement with those traditionally used in the Edo period in the 19th century, while the computational imaging technique RTI gave an additional amount of information in terms of surface characterization that could not be overlooked when studying these works of art. RTI data were further processed to enhance the texture visualization. Full article
(This article belongs to the Special Issue Sensor Techniques for Artworks Analysis and Investigations)
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20 pages, 7143 KiB  
Article
Images Enhancement of Ancient Mural Painting of Bey’s Palace Constantine, Algeria and Lacuna Extraction Using Mahalanobis Distance Classification Approach
by Adel Nasri and Xianfeng Huang
Sensors 2022, 22(17), 6643; https://doi.org/10.3390/s22176643 - 02 Sep 2022
Cited by 3 | Viewed by 1795
Abstract
As a result of human activity and environmental changes, several types of damages may occur to ancient mural paintings; indeed, lacunae, which refer to the area of paint layer loss, are the most prevalent kind. The presence of lacuna is an essential sign [...] Read more.
As a result of human activity and environmental changes, several types of damages may occur to ancient mural paintings; indeed, lacunae, which refer to the area of paint layer loss, are the most prevalent kind. The presence of lacuna is an essential sign of the progress of mural painting deterioration. Most studies have focused on detecting and removing cracks from old paintings. However, lacuna extraction has not received the necessary consideration and is not well-explored. Furthermore, most recent studies have focused on using deep learning for mural protection and restoration, but deep learning requires a large amount of data and computational resources which is not always available in heritage institutions. In this paper, we present an efficient method to automatically extract lacunae and map deterioration from RGB images of ancient mural paintings of Bey’s Palace in Algeria. Firstly, a preprocessing was applied using Dark Channel Prior (DCP) to enhance the quality and improve visibility of the murals. Secondly, a determination of the training sample and pixel’s grouping was assigned to their closest sample based on Mahalanobis Distance (MD) by calculating both the mean and variance of the classes in three bands (R, G, and B), in addition to the covariance matrix of all the classes to achieve lacuna extraction of the murals. Finally, the accuracy of extraction was calculated. The experimental results showed that the proposed method can achieve a conspicuously high accuracy of 94.33% in extracting lacunae from ancient mural paintings, thus supporting the work of a specialist in heritage institutions in terms of the time- and cost-consuming documentation process. Full article
(This article belongs to the Special Issue Sensor Techniques for Artworks Analysis and Investigations)
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