2019
Journal article  Open Access

Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review

Tonazzini A., Salerno E., Abdel-Salam Z. A., Harith M. A., Marras L., Botto A., Campanella B., Legnaioli S., Pagnotta S., Poggialini F., Palleschi V.

Archaeology  Image analysis  Multispectral imaging  Ancient manuscripts  Blind separation techniques  Review Article  Cultural heritage  Multidisciplinary 

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings. (C) 2019 The Authors. Published by Elsevier B.V.

Source: Journal of Advanced Research (Print) (Print) 17 (2019): 31–42. doi:10.1016/j.jare.2019.01.003

Publisher: Elsevier, Cairo, Egitto


Baronti, S., Casini, A., Lotti, F., Porcinai, S.. Multispectral imaging system for the mapping of pigments in works of art by use of principal-component analysis. Appl Opt. 1998; 37 (8): 1299
Casini, A., Lotti, F., Picollo, M., Stefani, L., Buzzegoli, E.. Image spectroscopy mapping technique for noninvasive analysis of paintings. Stud Conserv. 1999; 44 (1): 39-48
Balas, C., Papadakis, V., Papadakis, N., Papadakis, A.. Vazgiouraki E, Themelis G. A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value. J Cult Herit. 2003; 4: 330s-337s
Fischer, C., Kakoulli, I.. Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications. Rev Conserv. 2006; 7: 3-16
Vilaseca, M., Pujol, J., Arjona, M., de Lasarte, M.. Multispectral system for reflectance reconstruction in the near-infrared region. Appl Opt. 2006; 45 (18): 4241
Cristoforetti, G., Legnaioli, S., Palleschi, V., Salvetti, A., Tognoni, E.. Optical Chemical Sensors NATO Science Series II: Mathematics, Physics and Chemistry. 2006: 515-526
Bonifazzi, C., Carcagnì, P., Fontana, R., Greco, M., Mastroianni, M., Materazzi, M.. A scanning device for VIS–NIR multispectral imaging of paintings. J Opt A Pure Appl Opt. 2008; 10 (6): 064011
Marras, L., Pelagotti, A., Castaldi, M., Carmagnola, R., Adinolfi, G.. La Signora dei Demoni Azzurri. Archeo. 2009; 296: 80-85
Grifoni, E., Briganti, L., Marras, L., Orsini, S., Colombini, M.P., Legnaioli, S.. The chemical-physical knowledge before the restoration: The case of “The Plague in Lucca”, a masterpiece of Lorenzo Viani (1882–1936). Herit Sci. 2015; 3 (1)
Marengo, E., Manfredi, M., Zerbinati, O., Robotti, E., Mazzucco, E., Gosetti, F.. Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the dead sea scrolls. Anal Chem. 2011; 83 (17): 6609-6618
Daffara, C., Pampaloni, E., Pezzati, L., Barucci, M., Fontana, R.. Scanning multispectral IR reflectography SMIRR: An advanced tool for art diagnostics. Acc Chem Res. 2010; 43 (6): 847-856
12 Fontana R, Gambino MC, Greco M, Marras L, Materazzi M, Pampaloni E, et al. New high-resolution IR-color reflectography scanner for painting diagnosis. In: Salimbeni R, editor. International Society for Optics and Photonics; 2003. p. 108–15. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=767715.
van Asperen de Boer, J.R.J.. A note on the use of an improved infrared vidicon for reflectography of paintings. Stud Conserv. 1974; 19: 97-99
Hollmann, J.C., Crause, K.. Digital imaging and the revelation of “hidden” rock art: Vaalekop Shelter, KwaZulu-Natal. South African Humanit. 2011; 23 (1): 55-76
Chabries, D.M., Booras, S.W., Bearman, G.H.. Imaging the past: recent applications of multispectral imaging technology to deciphering manuscripts. Antiquity. 2003; 77 (296): 359-372
Knox, K., Johnston, R., Easton, R.L.. Imaging the dead sea scrolls. Opt Photonics News. 1997; 8 (8): 30
17 Bloechl K, Hamlin H, Easton, Jr. RL. Text recovery from the ultraviolet-fluorescent spectrum for treatises of the Archimedes Palimpsest. In: Stork DG, Coddington J, Bentkowska-Kafel A, editors. 2010. p. 753109. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.838886.
Adinolfi, G., Carmagnola, R., Cataldi, M., Marras, L., Palleschi, V.. Recovery of a lost wall painting at the Etruscan Tomb of the Blue Demons in Tarquinia (Viterbo, Italy) by multispectral reflectometry and UV fluorescence imaging. Archaeometry. 2018
19 Toque JA, Sakatoku Y, Ide-Ektessabi A. Pigment identification by analytical imaging using multispectral images. In: 2009 16th IEEE International Conference on Image Processing (ICIP). IEEE; 2009. p. 2861–4. Available from: http://ieeexplore.ieee.org/document/5414508/
20 Melis M, Miccoli M, Quarta D. Multispectral hypercolorimetry and automatic guided pigment identification: some masterpieces case studies. In: Pezzati L, Targowski P, editors. 2013. p. 87900W. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2020643.
Comelli, D., Nevin, A., Valentini, G., Osticioli, I., Castellucci, E.M., Toniolo, L.. Insights into Masolino’s wall paintings in Castiglione Olona: Advanced reflectance and fluorescence imaging analysis. J Cult Herit. 2011; 12 (1): 11-18
Mazzeo, R., Palazzi, C.E., Roccetti, M., Sciutto, G.. Proceedings of the IASTED European Conference on Internet and Multimedia Systems and Applications. 2007: 266-271
Paviotti, A., Forsyth, D.A., Cortelazzo, G.M.. Lightness recovery for pictorial surfaces. Int J Comput Vis. 2011; 94 (1): 54-77
24 Ricciardi P, Delaney JK, Glinsman L, Thoury M, Facini M, de la Rie ER. Use of visible and infrared reflectance and luminescence imaging spectroscopy to study illuminated manuscripts: pigment identification and visualization of underdrawin gs. In: Pezzati L, Salimbeni R, editors. International Society for Optics and Photonics; 2009. p. 739106. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.827415.
Marengo, E., Manfredi, M., Zerbinati, O., Robotti, E., Mazzucco, E., Gosetti, F.. Development of a technique based on multi-spectral imaging for monitoring the conservation of cultural heritage objects. Anal Chim Acta. 2011; 706 (2): 229-237
26 Toque JA, Komori M, Murayama Y, Ide-Ektessabi A. Analytical Imaging of Traditional Japanese Paintings Using Multispectral Images. 2010. p. 119–32. http://link.springer.com/10.1007/978-3-642-11840-1_9.
Rogerio-Candelera, M.A., Jurado, V., Laiz, L., Saiz-Jimenez, C.. Laboratory and in situ assays of digital image analysis based protocols for biodeteriorated rock and mural paintings recording. J Archaeol Sci. 2011; 38 (10): 2571-2578
Grifoni, E., Legnaioli, S., Lorenzetti, G., Pagnotta, S., Palleschi, V.. Image based recording of three-dimensional profiles of paint layers at different wavelengths. Eur J Sci Theol. 2017; 13 (2)
Grifoni, E., Legnaioli, S., Nieri, P., Campanella, B., Lorenzetti, G., Pagnotta, S.. Construction and comparison of 3D multi-source multi-band models for cultural heritage applications. J Cult Herit. 2018
30 The Archimedes Palimpsest Project. http://www.archimedespalimpsest.org/.
Easton, R.L., Knox, K.T., Christens-Barry, W.A.. 32nd Applied Imagery Pattern Recognition Workshop, 2003 Proceedings. 2003: 111-116
Easton, R.L., Christens-Barry, W.A., Knox, K.T.. Εικονοποιία Symposium on Digital Imaging of Ancient Textual Heritage: Technological Challenges and Solutions. 2010: 3-26
33 Easton RL, Knox KT, Christens-Barry WA, Boydston K, Toth MB, Emery D, et al. Standardized system for multispectral imaging of palimpsests. In: Stork DG, Coddington J, Bentkowska-Kafel A, editors. 2010. p. 75310D. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.839116.
34 Digitale Palimpsestforschung. Available from: http://www.teuchos.uni-hamburg.de/palimpsestuntersuchung.
Gau, M., Miklas, H., Lettner, M., Sablatnig, R.. Image acquisition and processing routines for damaged manuscripts. Digit Mediev. 2010; 6: 715-736
Čamba, A., Gau, M., Hollaus, F., Fiel, S., Sablatnig, R.. Multispectral imaging, image enhancement, and automated writer identification in historical manuscripts. Manuscr Cult. 2014; 7: 83-91
Bianco, G., Bruno, F., Tonazzini, A., Salerno, E., Savino, P., Sroubek, F.. Proc 8th Eurographics Italian Chapter Conference. 2010
Lettner, M., Diem, M., Sablatnig, R., Miklas, H.. 12th Computer Vision Winter Workshop. 2007: 51-58
Rapantzikos, K., Balas, C.. IEEE International Conference on Image Processing 2005. 2005: II-618
Giacometti, A., Campagnolo, A., MacDonald, L., Mahony, S., Robson, S., Weyrich, T.. The value of critical destruction: Evaluating multispectral image processing methods for the analysis of primary historical texts. Digit Scholarsh Humanit. 2015; 32 (1): fqv036
Janssens, K., Dik, J., Cotte, M., Susini, J.. Photon-based techniques for nondestructive subsurface analysis of painted cultural heritage artifacts. Acc Chem Res. 2010; 43 (6): 814-825
42 Bruker. M6 Jetstream, Large Area Micro X-ray Fluorescence Spectrometer brochure [Internet]. Available from: https://www.bruker.com/products/x-ray-diffraction-and-elemental-analysis/micro-xrf-and-txrf/m6-jetstream/overview.html.
Bruni, S., Caglio, S., Guglielmi, V., Poldi, G.. The joined use of n.i. spectroscopic analyses – FTIR, Raman, visible reflectance spectrometry and EDXRF – to study drawings and illuminated manuscripts. Appl Phys A.. 2008; 92 (1): 103-108
Knox, K.T., Easton, R.L., Christens-Barry, W.A.. Proceedings of the 16th European Signal Processing Conference (EUSIPCO). 2008
Meola, C., Carlomagno, G.M.. Recent advances in the use of infrared thermography. Meas Sci Technol. 2004; 15 (9): R27-R58
Mercuri, F., Orazi, N., Paoloni, S., Cicero, C., Zammit, U., Mercuri, F.. Thermography applied to the study of cultural heritage. Appl Sci. 2017; 7 (10): 1010
Grinzato, E., Bison, P.G., Marinetti, S.. Monitoring of ancient buildings by the thermal method. J Cult Herit. 2002; 3 (1): 21-29
Avdelidis, N., Moropoulou, A.. Applications of infrared thermography for the investigation of historic structures. J Cult Herit. 2004; 5 (1): 119-127
Moropoulou, A., Labropoulos, K.C., Delegou, E.T., Karoglou, M., Bakolas, A.. Non-destructive techniques as a tool for the protection of built cultural heritage. Constr Build Mater. 2013; 48: 1222-1239
Colombo, G., Mercuri, F., Scudieri, F., Zammit, U., Marinelli, M., Volterri, R.. Thermographic analysis of parchment bindings. Restauratorology. 2005; 26 (2): 92-104
Marinelli, M., Mercuri, F., Scudieri, F., Zammit, U., Colombo, G.. Thermographic study of microstructural defects in deteriorated parchment sheets. J Phys IV. 2005; 125: 527-529
Mercuri, F., Zammit, U., Orazi, N., Paoloni, S., Marinelli, M., Scudieri, F.. Active infrared thermography applied to the investigation of art and historic artefacts. J Therm Anal Calorim. 2011; 104 (2): 475-485
Maybury, I.J., Howell, D., Terras, M., Viles, H.. Comparing the effectiveness of hyperspectral imaging and Raman spectroscopy: a case study on Armenian manuscripts. Herit Sci. 2018; 6 (1): 42
Deneckere, A., Vekemans, B., Voorde, L., Paepe, P., Vincze, L., Moens, L.. Feasibility study of the application of micro-Raman imaging as complement to micro-XRF imaging. Appl Phys A. 2012; 106 (2): 363-376
Bicchieri, M., Monti, M., Piantanida, G., Sodo, A.. All that is iron-ink is not always iron-gall!. J Raman Spectrosc. 2008; 39 (8): 1074-1078
Botteon, A., Conti, C., Realini, M., Colombo, C., Matousek, P.. Discovering hidden painted images: subsurface imaging using microscale spatially offset raman spectroscopy. Anal Chem. 2017; 89 (1): 792-798
Pagnotta, S., Lezzerini, M., Ripoll-Seguer, L., Hidalgo, M., Grifoni, E., Legnaioli, S.. Micro-Laser-Induced Breakdown Spectroscopy (Micro-LIBS) Study on Ancient Roman Mortars. Appl Spectrosc. 2017; 71 (4): 721-727
Pagnotta, S., Legnaioli, S., Campanella, B., Grifoni, E., Lezzerini, M., Lorenzetti, G.. Micro-chemical evaluation of ancient potsherds by μ-LIBS scanning on thin section negatives. Mediterr Archaeol Archaeom. 2018; 18 (5): 171-178
Bell, A.J., Sejnowski, T.J.. An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 1995; 7 (6): 1129-1159
Cichocki, A., Amari, S.. 2002
McLachlan, G.J.. 1992
Tonazzini, A., Salerno, E., Mochi, M., Bedini, L.. 2004: 241-248
Tonazzini, A., Bedini, L., Salerno, E.. Independent component analysis for document restoration. Doc Anal Recognit. 2004; 7 (1)
64 Tonazzini A, Bianco G, Salerno E. Registration and Enhancement of Double-Sided Degraded Manuscripts Acquired in Multispectral Modality. In: 2009 10th International Conference on Document Analysis and Recognition [Internet]. IEEE; 2009. p. 546–50.
Salerno, E., Tonazzini, A., Grifoni, E., Lorenzetti, G., Legnaioli, S., Lezzerini, M.. Analysis of multispectral images in cultural heritage and archaeology. J Appl Laser Spectrosc. 2014; 1: 22-27
Legnaioli, S., Grifoni, E., Lorenzetti, G., Marras, L., Pardini, L., Palleschi, V.. Enhancement of hidden patterns in paintings using statistical analysis. J Cult Herit. 2013; 14 (3): S66-S70
Salerno, E., Tonazzini, A., Bedini, L.. Digital image analysis to enhance underwritten text in the Archimedes palimpsest. Int J Doc Anal Recognit. 2007; 9 (2–4): 79-87
Tonazzini, A., Bedini, L., Salerno, E., Gori, M., Marinai, S.. Artificial Neural Networks in Pattern Recognition. 2003: 33-38
Hollaus, F., Gau, M., Sablatnig, R.. 2012: 30-39
70 Knox KT, Easton RL, Christens-Barry WA, Boydston K. Recovery of handwritten text from the diaries and paper s of David Livingstone. 2011. p. 786909. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.877135.
Legnaioli, S., Lorenzetti, G., Cavalcanti, G.H., Grifoni, E., Marras, L., Tonazzini, A.. Recovery of archaeological wall paintings using novel multispectral imaging approaches. Herit Sci. 2013; 1
Xiang, Y., Peng, D., Yang, Z.. 2015
Li, R., Li, H., Wang, F.. Dependent component analysis: concepts and main algorithms. J Comput. 2010; 5 (4): 589-597
Caiafa, C.F., Salerno, E., Proto, A.N., Fiumi, L.. Blind spectral unmixing by local maximization of non-Gaussianity. Signal Process. 2008; 88 (1): 50-68
Du, Q., Kopriva, I.. Dependent component analysis for blind restoration of images degraded by turbulent atmosphere. Neurocomputing. 2009; 72 (10–12): 2682-2692
76 Kopriva I, Peršin A, Puizina-Ivić N, Mirić L. Dependent component analysis based approach to robust demarcation of skin tumors. In: Pluim JPW, Dawant BM, editors. 2009. p. 72594Q. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.806404.
Tonazzini, A., Bedini, L.. Restoration of recto–verso colour documents using correlated component analysis. EURASIP J Adv Signal Process. 2013; 2013 (1): 58
78 Hollaus F, Gau M, Sablatnig R. Enhancement of Multispectral Images of Degraded Documents by Employing Spatial Information. In: 2013 12th International Conference on Document Analysis and Recognition. IEEE; 2013. p. 145–9. Available from: http://ieeexplore.ieee.org/document/6628601/
Kohonen, T.. The self-organizing map. Neurocomputing. 1998; 21 (1–3): 1-6
80 McCune B, Grace JB, Urban DL. Analysis of ecological communities. MjM Software Design; 2002. 300 p.
Kruse, F.A., Lefkoff, A.B., Boardman, J.W., Heidebrecht, K.B., Shapiro, A.T., Barloon, P.J.. The spectral image processing system (SIPS)—interactive visualization and analysis of imaging spectrometer data. Remote Sens Environ. 1993; 44 (2–3): 145-163
Schwarz, J., Staenz, K.. Adaptive threshold for spectral matching of hyperspectral data. Can J Remote Sens. 2001; 27 (3): 216-224
Dennison, P.E., Halligan, K.Q., Roberts, D.A.. A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper. Remote Sens Environ. 2004; 93 (3): 359-367
Easton, R.L., Christens-Barry, W.A., Knox, K.T.. Proceedings of the 19th European Signal Processing Conference, EUSIPCO 2011. 2011: 1440-1444
Noel, W.. Archimedes and company. Br Acad Rev. 2007; 10
Walvoord, D.J., Easton, R.L.. Digital transcription of the archimedes palimpsest [applications corner]. IEEE Signal Process Mag. 2008; 25 (4): 100-104
Moon, T., Schilling, M.R., Thirkettle, S.. A note on the use of false-color infrared photography in conservation. Stud Conserv. 1992; 37 (1): 42
Easton, R.L., Kelbe, D.. Statistical processing of spectral imagery to recover writings from erased or damaged manuscripts. Manuscr Cult. 2014; 7: 35-46
Salerno, E., Tonazzini, A.. Proceedings of the 4-th Intl Congr Science and Technology for the Safeguard of Cultural Heritage in the Mediterranean Basin. 2010: 532-535
Grifoni, E., Campanella, B., Legnaioli, S., Lorenzetti, G., Marras, L., Pagnotta, S.. A new Infrared True-Color approach for visible-infrared multispectral image analysis. ACM J Comp Cult Her. 2018
Calatroni, L., d’Autume, M., Hocking, R., Panayotova, S., Parisotto, S., Ricciardi, P.. Unveiling the invisible: mathematical methods for restoring and interpreting illuminated manuscripts. Herit Sci. 2018; 6 (1): 56
Peng, J., Yu, K., Wang, J., Zhang, Q., Wang, L., Fan, P.. Mining painted cultural relic patterns based on principal component images selection and image fusion of hyperspectral images. J Cult Herit. 2018
93 Bergmann U, Knox KT. Pseudo-color enhanced x-ray fluorescence imaging of the Archimedes Palimpsest. In: Berkner K, Likforman-Sulem L, editors. 2009. p. 724702. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.806053.
94 Sharma G. Show-through cancellation in scans of duplex printed documents. IEEE Trans Image Process. 2001;10(5):736–54.
Sharma, G.. Show-through cancellation in scans of duplex printed documents. IEEE Trans Image Process. 2001; 10 (5): 736-754
96 Corporation X. The Xerox Color Encoding Standard; 1989.
97 Swift R. Analysis of the Spectra of Degraded Documents. Technology. 2001. Available from: https://ritdml.rit.edu/handle/1850/5773.
98 Knox KT. Enhancement of overwritten text in the Archimedes Palimpsest. In: Stork DG, Coddington J, editors. 2008. p. 681004. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.766679.
Ohta, Y.-I., Kanade, T., Sakai, T.. Color information for region segmentation. Comput Graph Image Process. 1980; 13 (3): 222-241
Tonazzini, A.. Color space transformations for analysis and enhancement of ancient degraded manuscripts. Pattern Recognit Image Anal. 2010; 20 (3): 404-417
Tonazzini, A., Salerno, E., Bedini, L.. Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique. Int J Doc Anal Recognit. 2007; 10 (1): 17-25
Tan, Chew Lim, Cao, R., Shen, Peiyi. Restoration of archival documents using a wavelet technique. IEEE Trans Pattern Anal Mach Intell. 2002; 24 (10): 1399-1404
Huang, Yi, Brown, M.S., Dong, Xu.. User-Assisted Ink-Bleed Reduction. IEEE Trans Image Process. 2010; 19 (10): 2646-2658
104 Rowley-Brooke R, Pitie F, Kokaram A. A Non-parametric Framework for Document Bleed-through Removal. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition [Internet]. IEEE; 2013. p. 2954–60.
Tonazzini, A., Gerace, I., Martinelli, F.. Multichannel blind separation and deconvolution of images for document analysis. IEEE Trans Image Process. 2010; 19 (4): 912-925
106 Merrikh-Bayat F, Babaie-Zadeh M, Jutten C. Using non-negative matrix factorization for removing show-through. 2010. p. 482–9. Available from: http://link.springer.com/10.1007/978-3-642-15995-4_60.
Martinelli, F., Salerno, E., Gerace, I., Tonazzini, A.. Nonlinear model and constrained ML for removing back-to-front interferences from recto–verso documents. Pattern Recognit. 2012; 45 (1): 596-605
Salerno, E., Martinelli, F., Tonazzini, A.. Nonlinear model identification and see-through cancelation from recto–verso data. Int J Doc Anal Recognit. 2013; 16 (2): 177-187
Merrikh-Bayat, F., Babaie-Zadeh, M., Jutten, C.. Linear-quadratic blind source separating structure for removing show-through in scanned documents. Int J Doc Anal Recognit. 2011; 14 (4): 319-333
Almeida, M.S.C., Almeida, L.B.. Nonlinear separation of show-through image mixtures using a physical model trained with ICA. Signal Process. 2012; 92 (4): 872-884
Moghaddam, R.F., Cheriet, M.. A variational approach to degraded document enhancement. IEEE Trans Pattern Anal Mach Intell. 2010; 32 (8): 1347-1361
Tonazzini, A., Savino, P., Salerno, E.. A non-stationary density model to separate overlapped texts in degraded documents. Signal, Image Video Process. 2015; 9 (S1): 155-164
113 Harman J. http://www.dstretch.com/
114 tanco F, Battiato S, Gallo G. Digital imaging for cultural heritage preservation : analysis, restoration, and reconstruction of ancient artworks [Internet]. CRC Press; 2011. 487 p. Available from: https://books.google.it/books/about/Digital_Imaging_for_Cultural_Heritage_Pr.html?id=QHnBxQ2xhGQC&redir_esc=y.
McCarthy, J.. Multi-image photogrammetry as a practical tool for cultural heritage survey and community engagement. J Archaeol Sci. 2014; 43: 175-185
Dimoulas, C.A., Kalliris, G.M., Chatzara, E.G., Tsipas, N.K., Papanikolaou, G.V.. Audiovisual production, restoration-archiving and content management methods to preserve local tradition and folkloric heritage. J Cult Herit. 2014; 15 (3): 234-241
Tuna, G., Zogo, R., Çiftçi, E.E., Demirelli, B., Tuna, A.. Identification, preservation and management of cultural heritage of Edirne, Turkey by means of a web-based application. J Balk Libr Union. 2015; 3 (2): 36-41
Zacharopoulos, A., Hatzigiannakis, K., Karamaoynas, P., Papadakis, V.M., Andrianakis, M., Melessanaki, K.. A method for the registration of spectral images of paintings and its evaluation. J Cult Herit. 2018; 29: 10-18

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BibTeX entry
@article{oai:it.cnr:prodotti:403318,
	title = {Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review},
	author = {Tonazzini A. and Salerno E. and Abdel-Salam Z.  A. and Harith M.  A. and Marras L. and Botto A. and Campanella B. and Legnaioli S. and Pagnotta S. and Poggialini F. and Palleschi V.},
	publisher = {Elsevier, Cairo, Egitto},
	doi = {10.1016/j.jare.2019.01.003},
	journal = {Journal of Advanced Research (Print) (Print)},
	volume = {17},
	pages = {31–42},
	year = {2019}
}