Casadio F, Toniolo L. The analysis of polychrome works of art: 40 years of infrared spectroscopic investigations. J Cult Herit. 2001;2(1):71–8.
Article
Google Scholar
Leona M, Casadio F, Bacci M, Picollo M. Identification of the pre-columbian pigment mayablue on works of art by noninvasive UV-Vis and raman spectroscopic techniques. J Am Inst Conserv. 2004;43(1):39–54.
Google Scholar
J. K. Delaney, P. Ricciardi,L. D. Glinsman,M. Facini,M. Thoury,M. Palmer &E. R. Rie, “Use of imaging spectroscopy, fiber optic reflectance spectroscopy, and X-ray fluorescence to map and identify pigments in illuminated manuscripts,” vol. 59, no. 2, pp. 91–101, 2014.
Cheilakou E, Troullinos M, Koui M. Identification of pigments on Byzantine wall paintings from Crete (14th century AD) using non-invasive Fiber Optics Diffuse Reflectance Spectroscopy (FORS). J Archaeol Sci. 2014;41:541–55.
Article
CAS
Google Scholar
Bonizzoni L, Bruni S, Gargano M, Guglielmi V, Zaffino C, Pezzotta A, Pilato A, Auricchio T, Delvaux L, Ludwig N. Use of integrated non-invasive analyses for pigment characterization and indirect dating of old restorations on one Egyptian coffin of the XXI dynasty. Microchem J. 2018;138:122–31.
Article
CAS
Google Scholar
Tortora M, Sfarra S, Chiarini M, Daniele V, Taglieri G, Cerichelli G. Non-destructive and micro-invasive testing techniques for characterizing materials, structures and restoration problems in mural paintings. Appl Surf Sci. 2016;387:971–85.
Article
CAS
Google Scholar
P. Colomban, “On–site Raman study of artwork : Procedure and illustrative examples,” no. November, pp. 1–14, 2017.
Sfarra S, Castanedo C, Tortora M, Arrizzac L, Cerichelli G, Nardi I, Maldague X. Diagnostics of wall paintings: a smart and reliable approach. J Cult Herit. 2016;18:229–41.
Article
Google Scholar
S. Amookht, S. G. Kandi, M. Mahdavian, “Progress in Organic Coatings Mathematical description of spectrophotometric properties of metallic coatings using spectral derivation and principal component analysis,” Prog. Org. Coatings, vol. 129, no. October 2018, pp. 338–348, 2019.
A. V. Agberien and B. Örmeci, “Monitoring of Cyanobacteria in water using spectrophotometry and first derivative of absorbance,” 2020.
Cosentino A. Effects of different binders on technical photography and infrared reflectography of 54 historical pigments. Int J Conserv Sci. 2015;6(3):287–98.
CAS
Google Scholar
Bacci M, Casini A, Cucci C, Picollo M, Radicati B, Vervat M. Non-invasive spectroscopic measurements on the Il ritratto della figliastra by Giovanni Fattori: identification of pigments and colourimetric analysis. J Cult Herit. 2003;4(4):329–36.
Article
Google Scholar
Cavaleri T, Giovagnoli A, Nervo M. Pigments and mixtures identification by visible reflectance spectroscopy. Procedia Chem. 2013;8:45–54.
Article
CAS
Google Scholar
Dupuis G, Menu M. Quantitative evaluation of pigment particles in organic layers by fibre-optics diffuse-reflectance spectroscopy. Appl Phys A Mater Sci Process. 2005;80(4):667–73.
Article
CAS
Google Scholar
Leona M, Winter J. Fiber optics reflectance spectroscopy: a unique tool for the investigation of Japanese paintings. Stud Conserv. 2001;46(3):153–62.
CAS
Google Scholar
M. Reháková, L. Gál, M. B. cová, M. Oravec, V. Dvonka, D. S. Cová, M. Ceppan, “Identification of iron-gall inks in historical drawings by Fibre Optics Reflection Spectroscopy–Extension to the NIR spectral range,” J. Cult. Herit. vol. 27, pp. 137–142, 2017.
Wang J, Wu X, Xu Z. Potential-based obstacle avoidance in formation control. J Control Theory Appl. 2008;6(3):311–6.
Article
Google Scholar
Pan N, Hou M, Lv S, Hu Y, Zhao X, Ma Q, Li S, Shaker A. Extracting faded mural patterns based on the combination of spatial-spectral feature of hyperspectral image. J Cult Herit. 2017;27:80–7.
Article
Google Scholar
R. S. Berns and F. H. Imai, “The use of multi-channel visible spectrum imaging for pigment identification,” 13th Trienn. Meet. Rio Janiero, 22-27 Sept. 2002 Prepr., pp. 217–222, 2002.
J. M. Fernández Rodríguez and J. A. Fernández Fernández, “Application of the second derivative of the Kubelka-Munk function to the semiquantitative analysis of Roman paintings,” Color Res. Appl., vol. 30, no. 6, pp. 448–456, 2005.
Barron V, Torrent J. Use of the Kubelka—Munk theory to study the influence of iron oxides on soil colour. J Soil Sci. 1986;37(4):499–510.
Article
CAS
Google Scholar
Szalai Z, Kiss K, Jakab G, Sipos P, Belucz B, Németh T. The use of UV-VIS-NIR reflectance spectroscopy to identify iron minerals. Astron Nachrichten. 2013;334(9):940–3.
Article
CAS
Google Scholar
Berns RS, Mohammadi M. Single-constant simplification of Kubelka-Munk turbid-media theory for paint systems–A review. Color Res Appl. 2007;32(3):201–7.
Article
Google Scholar
Pallipurath AR, Skelton JM, Ricciardi P, Elliott SR. Estimation of semiconductor-like pigment concentrations in paint mixtures and their differentiation from paint layers using first-derivative reflectance spectra. Talanta. 2016;154:63–72.
Article
CAS
Google Scholar
Daniel F, Mounier A, Arantegui JP, Pardos C, Taboada NP, Vallejuelo SF, Castro K. Hyperspectral imaging applied to the analysis of Goya paintings in the Museum of Zaragoza (Spain). Microchem J. 2016;126:113–20.
Article
CAS
Google Scholar
Balas C, Epitropou G, Tsapras A, Hadjinicolaou N. Hyperspectral imaging and spectral classification for pigment identification and mapping in paintings by El Greco and his workshop. Multimed Tools Appl. 2018;77(8):9737–51.
Article
Google Scholar
M. Alfeld, M. Mulliez, J. Devogelaere, L. de Viguerie, P. Jockey, and P. Walter, “MA-XRF and hyperspectral reflectance imaging for visualizing traces of antique polychromy on the Frieze of the Siphnian Treasury,” Microchem. J., vol. 141, no. September 2017, pp. 395–403, 2018.
Grabowski B, Masarczyk W, Głomb P, Mendys A. Automatic pigment identification from hyperspectral data. J Cult Herit. 2018;31:1–12.
Article
Google Scholar
C. Barata, J. S. Marques, and J. Rozeira, “A System for the Detection of Pigment Network in Dermoscopy Images Using Directional Filters,” vol. 59, no. 10, pp. 2744–2754, 2012.
S. Baronti, A. Casini, F. Lotti, and S. Porcinai, “Multispectral imaging system for the mapping of pigments in works of art by use of principal-component analysis,” vol. 37, no. 8, pp. 1299–1309, 1998.
R. Mazzeo, C. E. Palazzi, M. Roccetti, G. Sciutto, U. Bologna, and M. A. Zamboni, “Computer Assisted Pigment Identification in Artworks. Multi-spectral Scanner Imaging System ” no. 1, pp. 1–6.
A. Cosentino, “Multispectral imaging of pigments with a digital camera and 12 interferential filters,” e-Preservation Sci., vol. 12, pp. 1–7, 2015.
S. G. Kandi, “Representing Spectral Data Using Lab PQR Color Space in Comparison with PCA Method,” vol. 4, pp. 95–106, 2011.
A. Cosentino, “FORS Spectral Database of Historical Pigments in Different Binders,” e-conservation J., no. September, pp. 54–65, 2014.