Skip to main content
SpringerLink
Log in

Historical manuscript dating: traditional and current trends

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

There is a huge number of undated digitized and undigitized historical manuscripts from antiquity. The dates of production of these historical manuscripts are of interest to historians, curators, paleographers, scholars and other stakeholders. This paper discourses comprehensively the trend of historical manuscript dating (HMD) approaches and techniques from traditional to modern (computer-based) methods. There are many methods for historical manuscript dating (HMD) that have been developed. They are divided into 3 main categories: paleographic, physical and computer-based techniques. Traditional HMD methods require samples of actual manuscripts, are time consuming, costly, and destructive. These drawbacks have informed the preferential shift to modern computer-based HMD methods. Computer-based methods use scanned images of manuscripts thereby preserving them, are relatively less costly, faster, convenient, and applicable in large scale. The future trend for computer-based HMD is discussed with aim of achieving better results in manuscript dating task. It is noted that not much research has been done in historical manuscript dating especially in modern computer-based methods which are applicable in large scale.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data Availability

Not applicable.

Code Availability

Not applicable.

Notes

  1. https://www.deadseascrolls.org.il/

  2. https://zenodo.org/record/1194357#.XuwwJefhXIU

  3. https://riksarkivet.se/SDHK

  4. http://www.holybooks.com/voynich-manuscript-codex-serahinianus-pd/

  5. https://openslr.org/

References

  1. Adak C, Chaudhuri BB, Blumenstein M (2019) An Empirical Study on Writer Identification and Verification from Intra-Variable Individual Handwriting. IEEE Access 7:24738–24758

    Article  Google Scholar 

  2. Adam K, Al-Maadeed S, Bouridane A (2017) Letter-based classification of Arabic scripts style in ancient Arabic manuscripts. IEEE International Workshop on Arabic Script Analysis and Recognition (ASAR), pp 95–98

  3. Adam K, Baig A, Al-Maadeed S, Bouridane A, El-Menshawy S (2018) KERTAS: Dataset For automatic dating of ancient arabic manuscripts. International Journal on Document Analysis and Recognition (IJDAR) 21:283–290. https://doi.org/10.1007/s10032-018-0312-3

    Article  Google Scholar 

  4. Alarifi J, Fry J, Dancey D, Yap MH (2019) Understanding Face Age Estimation: humans and machine. International Conference on Computer, Information and Telecommunication Systems (CITS). https://doi.org/10.1109/CITS.2019.8862107

  5. Aubin V, Mora M, Santos-Peñas M (2018) Off-line writer verification based on simple graphemes. Pattern Recognit 79:414–426

    Article  Google Scholar 

  6. Bagnall RS (2009) Early christian books in egypt, Princeton, pp 11–18

  7. Banerjee P, Han H (2009) Language modeling approaches to information retrieval. J Comput Sci Eng 3(3):143–164

    Article  Google Scholar 

  8. Barker D (2011) The dating of new testament papyri. New Testament Stud 57:571–582. https://doi.org/10.1017/S0028688511000129

    Article  Google Scholar 

  9. Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. IEEE Trans Patter Anal Mach Intell 24(4):509–522

    Article  Google Scholar 

  10. Bensefia A, Djeddi C (2020) Relevance of grapheme’s shape complexity in writer verification task. IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), pp 53–58

  11. Bonani G, Ivy S, Wolfli W, Broshi M, Carmi I, Strugnell J (1992) Radiocarbon dating of fourteen Dead Sea Scrolls. Radiocarbon 34(3):843–849. https://doi.org/10.2458/azu_js_rc.34.1537

  12. Bourgeois FL, Trinh E, Allier B, Eglin B, Emptoz H (2004) Document images analysis solutions for digital libraries. In: Proceedings of First International Workshop on Document Image Analysis for Libraries. IEEE, pp 2–24

  13. Brent N (2005) The use and abuse of p52: Papyrological pitfalls in the dating of the fourth gospel. Harv Theol Rev 98(1):23–48. https://doi.org/10.1017/S0017816005000842

    Article  Google Scholar 

  14. Brink A, Smit J, Bulacu M, Schomaker L (2012) Writer identification using directional ink-trace width measurements. Pattern Recogn 45(1):162–171

    Article  Google Scholar 

  15. Broder AZ (1998) On the resemblance and containment of documents. In: 1997 International Conference on Compression and Complexity of SEQUENCES 1997 (Cat No.97TB100171), Salerno, Italy. https://doi.org/10.1109/SEQUEN.1997.666900

  16. Broder AZ, Glassman SC, Manasse MS, Zweig G (1997) Syntactic clustering of the web. SRC Technical Note No. 1997-015, Digital Equipment Corporation. In: Proceedings of the Sixth International World Wide Web Conference, pp 391–404 Cat. No.97TB100171

  17. Brown KL, Clark RJH (2002) Analysis of pigmentary materials on the vinland map and tartar relation by raman microprobe spectroscopy. Anal Chem 74:3658–3661. https://doi.org/10.1021/ac025610r

    Article  Google Scholar 

  18. Bulacu M, Schomaker L (2007) Text-independent writer identification and verification using textural and allographic features. IEEE Trans Pattern Anal Mach Intell 29(4):701–717. https://doi.org/10.1109/TPAMI.2007.1009

    Article  Google Scholar 

  19. Burgio L, Clark RJH, Hark RR (2009) Spectroscopic investigation of modern pigments on purportedly medieval miniatures by the “Spanish Forger.” J Raman Spectrosc 40:2031–2036

    Article  Google Scholar 

  20. Cahill TA, Schwab RN, Kusko BH, Eldred RA, Moller G, Dutshke D, Wick DL (1987) The vinland map, revisited: New compositional evidence on its inks and parchment. Anal Chem 59:829–833. https://doi.org/10.1021/ac00133a009

    Article  Google Scholar 

  21. Carmine PD, Giuntini L, Hooper W, Lucarelli F, Mando PA (1996) Further results from PIXE analysis of inks in Galileo’s notes on motion. Nucl Instr Meth Phys Res B 113:354–358

    Article  Google Scholar 

  22. Casabianca T, Marinelli E, Pernagallo G, Torris B (2019) Radiocarbon dating of the turin shroud: New evidence from raw data. Achaeometry 61(5):1223–1231. https://doi.org/10.1111/arcm.12467

    Article  Google Scholar 

  23. Castro K, Perez-Alonso M, Rodriguez-Laso MD, Madariaga JM (2004a) Raman bre optic approach to artwork dating. Spectrochim Acta A 60:2919–2924

    Article  Google Scholar 

  24. Castro K, Vandenabeele P, Rodri’guez-Laso MD, Moens L, Madariaga JM (2004b) Micro-raman analysis of coloured lithographs. Anal Bioanal Chem 379:674–683

    Article  Google Scholar 

  25. Chahi A, El merabet Y, Ruichek Y, Touahni R (2019) An effective and conceptually simple feature representation for off-line text-independent writer identification. Expert Syst Appl 123:357–376

    Article  Google Scholar 

  26. Charlton MC (1941) Codex and roll in the new testament. Harv Theol Rev 34(4):219–149. https://doi.org/10.1017/S0017816000022471

    Article  Google Scholar 

  27. Chen S, Wang Y, Lin CT, Ding W, Cao Z (2019) Semi-supervised feature learning for improving writer identification. Inf Sci 482:156–170

    Article  MathSciNet  Google Scholar 

  28. Christlein V, Gropp M, Fiel S, Maier A (2017) Unsupervised feature learning for writer identification and writer retrieval. In Proc. 14th IAPR. Int Conf Document Anal Recognit (ICDAR) 1:991–997

    Google Scholar 

  29. Clark RJH (1995) Raman microscopy: Application to the identification of pigments on mediaeval manuscripts. Chem Soc Rev 24:187–196

    Article  Google Scholar 

  30. Clark RJH (1999) Raman microscopy: Sensitive probe of pigments on manuscripts, paintings and other artefacts. J Mol Struct 480–481:15–20

  31. Clark RJH (2007) The scientific investigation of artwork and archaeological artefacts: Raman microscopy as a structural, analytical and forensic tool. Appl Phys A 89:833–840. https://doi.org/10.1007/s00339-007-4212-5

    Article  Google Scholar 

  32. Cloppet F, Eglin V, Helias-Baron M, Kieu VC, Stutzmann D, Vincent N (2017) ICDAR 2017 competition on the classification of medieval handwritings in latin script. In: 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) 2017, Kyoto, pp 1371–1376. https://doi.org/10.1109/ICDAR.2017.224

  33. Cloppet F, Eglin V, Kieu VC, Stutzmann D, Vincent N (2016) ICFHR2016 Competition on the classification of medieval handwritings in latin script. In: Proceedings of the International Conference on Frontiers in Handwriting Recognition (ICFHR)

  34. Croatian Glagolitic manuscripts’ collections (CGMC), http://pisanabastina.unizd.hr, Accessed 23 March 2021

  35. Comfort PW, Barrett DP (1999) The complete Text of the Earliest New Testament manuscripts. Baker Pub Group

  36. Comfort PW, Barrett DP (2001) The text of the earliest new testament greek manuscripts: a corrected, enlarged edition of the complete text of the earliest new testament manuscripts. Tyndale house publishers, Wheaton, pp 204–205

  37. Damon PE, Donahue DJ, Gore BH, Hatheway AL, Jull AJT, Linick TW, Sercel PJ, Toolin LJ, Bronk CR, Hall ET, Hedges REM, Housley R, Law IA, Perry C, Bonani G, Trumbore S, Woelfli W, Ambers JC, Bowman SGE, Leese MN, Tite MS (1989) Radiocarbon dating of the Shroud of Turin. Nature 337:611–615. https://www.shroud.com/nature.htm

    Article  Google Scholar 

  38. Dargan S, Kumar M (2019) Writer identification system for indic and non-indic scripts: State-of-the-art survey. Arch Comput Methods Eng 26(4):1283–1311

  39. de Jong FMG, Rode H, Hiemstra D (2005) Temporal language models for the disclosure of historical text. In: Humanities, computers and cultural heritage: Proceedings of the XVIth International Conference of the Association for History and Computing (AHC 2005), pp 161–168

  40. Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) ImageNet: A Large-Scale Hierarchical Image Database. In: CVPR09

  41. Dhali MA, Jansen CN, Wit JM, Schomaker L (2020) Feature-extraction methods for historical manuscripts dating based on writing style development. Pattern Recogn Lett 131:413–420. https://doi.org/10.1016/j.patrec.2020.01.027

    Article  Google Scholar 

  42. Djeddi C, Siddiqi I, Souici-Meslati L, Ennaji A (2013) Text independent writer recognition using multi-script handwritten texts. Pattern Recognit Lett 34(10):1196–1202

    Article  Google Scholar 

  43. Dolfing H, Bellegarda J, Chorowski J, Marxer R, Laurent A (2019) The ScribbleLens” Dutch historical handwriting corpus https://openslr.org/84

  44. Dolfing HJGA, Bellegarda J, Chorowski J, Marxer R, Laurent A (2020) The “ScribbleLens” Dutch Historical Handwriting Corpus. 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp 67–72

  45. Don B (2011) The dating of new testament papyri. New Testament Stud 57:571–582. https://doi.org/10.1017/S0028688511000129

    Article  Google Scholar 

  46. Donahue DJ, Olin JS, Harbottle G (2002) Determination of the radiocarbon age of parchment of the Vinland Map. Radiocarbon 44(1):45–52

    Article  Google Scholar 

  47. Duran A, Perez-Rodriguez JL, Espejo T, Franquelo ML, Castaing J, Walter P (2009) Characterization of illuminated manuscripts by laboratory-made portable XRD and micro-XRD systems. Anal Bioanal Chem 395:1997–2004

    Article  Google Scholar 

  48. Earlier Latin Manuscripts (ELM), https://elmss.nuigalway.ie/, Accessed 23 March 2021

  49. Edwards HGM (2000) Art works studied using IR and Raman spectroscopy. In: Lindon J C (ed) Encyclopedia of spectroscopy and spectrometry, vol 1. Academic Press, London, pp 2–17

  50. European Association for Digital Humanities (EADH), https://eadh.org, Accessed 23 March 2021

  51. Evans CA (2017) Christian demographics and the dates of early new testament papyri. In: The Language and Literature of the New Testament, pp 201–217. https://doi.org/10.1163/9789004335936_009

  52. Fedi M (2009) Accelerator mass spectrometry for 14C dating. In: Colombini M P, Modugno F (eds) Organic mass spectrometry in art and archaeology. Wiley, Chichester, pp 459–482

  53. Fedi ME, Carraresi L, Grassi N, Migliori A, Taccetti F, Terrasi F, Mando PA (2010) The Artemidorus Papyrus: Solving an ancient puzzle with radiocarbon and ion beam analysis measurements. Radiocarbon 52:356–363

    Article  Google Scholar 

  54. Fernández-Mota D, Almazán J, Cirera N, Fornés A, Lladós J (2014) BH2M: the Barcelona Historical Handwritten Marriages database. 22nd International Conference on Pattern Recognition, pp 256–261. https://doi.org/10.1109/ICPR.2014.53

  55. Feuerverger A, Hall P, Tilahun G, Gervers M (2008) Using statistical smoothing to date medieval manuscripts. Inst Math Stat Collect 1:321–331. https://doi.org/10.1214/193940307000000248

    MathSciNet  Google Scholar 

  56. Fiallos R (2000) An overview of the process of dating undated medieval charters: Latest results and future developments. In: Gervers M (ed) Dating Undated Medieval Charters. Boydell Press, Woodbridge

  57. Fiel S, Sablatnig R (2012) Writer Retrieval and Writer Identification Using Local Features. 10th IAPR. Int. Work. Doc. Anal. Syst., pp 145–149

  58. Fiel S, Sablatnig R (2013) Writer identification and writer retrieval using the fisher vector on visual vocabularies. In: Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), pp 545–549

  59. Frank B (1944) The text of the epistle to the hebrews in p46. J Biblic Lit 63(4):379–396. https://doi.org/10.2307/3262540

    Article  Google Scholar 

  60. Garain U, Parui SK, Paquet T, Heutte L (2007) Machine dating of handwritten manuscripts. 9th International Conference on Document Analysis and Recognition (ICDAR). https://doi.org/10.1109/ICDAR.2007.4377017

  61. Gauglitz G, Vo-Dinh T (2003) Handbook of spectroscopy. WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

    Book  Google Scholar 

  62. Geng X, Zhou ZH, Smith-Miles K (2007) Automatic age estimation based on facial aging patterns. IEEE Trans Pattern Anal Mach Intell 29 (12):2234–2240. https://doi.org/10.1109/TPAMI.2007.70733

    Article  Google Scholar 

  63. Geng X, Zhou ZH, Zhang Y, Li G, Dai H (2006) Learning from facial aging patterns for automatic age estimation. In Proc. ACM Conf. Multimedia, pp 307–316

  64. Gervers M (2000a) The DEEDS project and the development of a computerised methodology for dating undated English private charters of the twelfth and thirteenth centuries. In: Gervers M (ed) Dating undated medieval charters. Boydell Press, Woodbridge, pp 13–35

  65. Gervers M (2000b) The dating of medieval English private charters of the twelfth and thirteenth centuries. Manuscript

  66. Giuntini L, Lucarelli F, Mando PA, Hooper W, Barker PH (1995) Galileo’s writings: chronology by PIXE. Nucl Instr Meth Phys Res B 95:389–389

    Article  Google Scholar 

  67. Guo G, Fu Y, Dyer CR, Huang TS (2008) Human age estimation by manifold learning and locally adjusted robust regression. IEEE Trans Image Process 17(7):1178–1188

    Article  MathSciNet  Google Scholar 

  68. Guo J -M, Liou Y -M, Nguyen H -S (2011) Human face age estimation with adaptive hybrid features. IEEE International Conference on System Science and Engineering, pp 55–57. https://doi.org/10.1109/ICSSE.2011.5961873

  69. Hamid A, Bibi M, Moetesum M, Siddiqi I (2019) Deep learning based approach for historical manuscript dating. International Conference on Document Analysis and Recognition (ICDAR), pp 967–972. https://doi.org/10.1109/ICDAR.2019.00159

  70. Hamid A, Bibi M, Siddiqi I, Moetesum M (2018) Historical manuscript dating using textural measures. International Conference on Frontiers of Information Technology (FIT), pp 235–241. https://doi.org/10.1109/FIT.2018.00048

  71. He K, Girshick RB, Dollár P (2019) Rethinking ImageNet Pre-Training. IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/ICCV.2019.00502

  72. He S, Samara P, Burgers J, Schomaker L (2014) Towards style-based dating of historical documents. In: International Conference of Frontiers in Handwriting Recognition (ICFHR), pp 265–270

  73. He S, Samara P, Burgers J, Schomaker L (2016a) Image-based historical manuscript dating using contour and stroke fragments. Pattern Recogn 58:159–171

    Article  Google Scholar 

  74. He S, Samara P, Burgers J, Schomaker L (2016b) Historical manuscript dating based on temporal pattern codebook. Comput Vis Image Underst 152:167–175. https://doi.org/10.1016/j.cviu.2016.08.008

    Article  Google Scholar 

  75. He S, Samara P, Burgers J, Schomaker L (2016c) A Multiple-Label guided clustering algorithm for historical document dating and localization. IEEE Trans Image Process 25(11):5252–5265. https://doi.org/10.1109/TIP.2016.2602078

    Article  MathSciNet  MATH  Google Scholar 

  76. He S, Samara P, Burgers J, Schomaker L (2016d) Discovering visual element evolutions for historical document dating. 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp 7–12. https://doi.org/10.1109/ICFHR.2016.0015

  77. He S, Schomaker L (2014) Delta-n hinge: rotation-invariant features for writer identification. International Conference on Pattern Recognition, pp 2023–2028. https://doi.org/10.1109/ICPR.2014.353

  78. He S, Schomaker L (2015) A polar stroke descriptor for classification of historical documents. In: International Conference on Document Analysis and Recognition (ICDAR), pp 6–10

  79. He S, Schomaker S (2019) Deep adaptive learning for writer identification based on single handwritten word images. Pattern Recognit 88:64–74

    Article  Google Scholar 

  80. He S, Schomaker L (2020) Fragnet: Writer Identification Using Deep Fragment Networks. IEEE Trans Inf Forensic Secur 15:3013–3022

    Article  Google Scholar 

  81. He S, Wiering M, Schomaker L (2015) Junction detection in handwritten documents and its applications to writer identification. Pattern Recogn 48(12):4036–4048

    Article  Google Scholar 

  82. He K, Zhang X, Ren S, Sun J (2016e) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770–778

  83. Head PM (1995) The date of the Magdalen papyrus of Mathew (p.MAGD.GR. 17P̄64): A response to C.P. Thiende, Tyndale Bullet 46:251–285

    Google Scholar 

  84. Hellborg R, Skog G (2008) Accelerator mass spectrometry. Mass Spectrom Rev 27:398–427

    Article  Google Scholar 

  85. Herman H (1937) A study of the chester beatty codex of the pauline epistles. J Theol Stud 38:148–163

    Google Scholar 

  86. Hiemstra D (1998) A linguistically motivated probabilistic model of information retrieval. In: Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries (ECDL), pp 569–584

  87. Hodgins GWL (2011) Forensic investigation of the Voynich manuscript Presented at Conference: Voynich 100. Frascati, Italy

    Google Scholar 

  88. Hollas JM (2004) Modern spectroscopy, 4th edn. Wiley, Chichester

    Google Scholar 

  89. Howe NR, Xie S (2017) Chronological Profiling for Paleography. In: 14th IAPR International Conference on Document Analysis and Recognition, pp 783–788. https://doi.org/10.1109/ICDAR.2017.133

  90. Islam AU, Khan MJ, Khurshid K, Shafait F (2019) Hyperspectral image analysis for writer identification using deep learning digital image computing: techniques and applications (DICTA). IEEE. https://doi.org/10.1109/DICTA47822.2019.8945886

  91. Internet Archive, http://archive.org/. Accessed 23 March 2021

  92. Jull AJT (2013) Some interesting and exotic applications of carbon-14 dating by accelerator mass spectrometry. J Phys: Conf Ser 436:012083. https://doi.org/10.1088/1742-6596/436/1/012083

    Google Scholar 

  93. Jull AJT, Burr GS (2014) Some interesting applications of radiocarbon dating to art and archaeology. Archeometr Muhely 11(3):139–148

    Google Scholar 

  94. Jull AJT, Donahue DJ, Broshi M, Tov E (1995) Radiocarbon dating of scrolls and linen fragments from the Judean desert. Radiocarbon 37:11–19

    Article  Google Scholar 

  95. Jurado-López A, Demko O, Clark RJH, Jacobs D (2004) Analysis of the palette of a precious 16th century illuminated Turkish manuscripts by Raman microscopy. J Raman Spectrosc 53:119–124. https://doi.org/10.1002/jrs.1115

    Article  Google Scholar 

  96. Jurafsky D, Martin JH (2000) Speech and language processing. Prentice Hall, Upper Saddle River

  97. Kaiser R, Kolb D (1990) Near-infrared reectance spectroscopy and authenticity of performance: Indications in Bach’s music manuscripts. Interdis Sci Rev 15:133–138

    Article  Google Scholar 

  98. Kanhabua N, Nørvåg K (2008) Improving Temporal Language Models for Determining Time of Non-timestamped Documents. In: Christensen-Dalsgaard B, Castelli D, Ammitzbøll Jurik B, Lippincott J (eds) Research and Advanced Technology for Digital Libraries. ECDL 2008. Lecture Notes in Computer Science, vol 5173, pp 358–370. https://doi.org/10.1007/978-3-540-87599-4_37

  99. Khan FA, Khelifi F, Tahir MA, Bouridane A (2019) Dissimilarity Gaussian mixture models for efficient offline handwritten textindependent identification using SIFT and rootSIFT descriptors. IEEE Trans Inf Forensic Secur 14 (2):289–303

    Article  Google Scholar 

  100. Kim YK (1988) Palaeographical dating of p46 to the later first century. Biblica 69(2):248–257

    Google Scholar 

  101. Kornblith S, Shlens J, Le QV (2018) Do better imagenet models transfer better? arXiv:1805.0897

  102. Kraaij W (2004) Variations on language modelling for information retrieval. PhD thesis, University of Twente, Netherlands

    Google Scholar 

  103. Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097–1105

  104. Kuhl FP, Giardina CR (1982) Elliptic Fourier features of a closed contour. Comput Graph Image Process 18(3):236–258

    Article  Google Scholar 

  105. Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Stat 22(1):79–86. https://doi.org/10.1214/aoms/1177729694

    Article  MathSciNet  MATH  Google Scholar 

  106. Lai S, Jin L (2019) Offline Writer Identification based on the Path Signature Feature. 2019 International Conference on Document Analysis and Recognition (ICDAR), pp 1137–1142

  107. Latin manuscript of parchment, https://en.wikipedia.org/wiki/Parchment. Accessed 23 March 2021

  108. Larkin P (2011) Infrared and raman spectroscopy: principles and spectral interpretation. Elsevier Inc., 225 Wyman Street, USA

  109. Latecki LJ, Lakamper R (1999) Convexity rule for shape decomposition based on discrete contour evolution. Comput Vis Image Underst 73(3):441–454

    Article  Google Scholar 

  110. Lauwers D, Cattersel V, Vandamme L, Eester AV, De Langhe K, Moens L, Vandenabeele P (2014) Pigment identification of an illuminated mediaeval manuscript De Civitate Dei by means of a portable Raman equipment. J Raman Spectrosc 45:1266–1271. https://doi.org/10.1002/jrs.4500

    Article  Google Scholar 

  111. Lavrenko V, Croft WB (2001) Relevance based language models. Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, pp 120–127

  112. Li Y, Genzel Y, Fujii Y, Popat AC (2015) Publication date estimation for printed historical documents using convolutional neural networks. In: Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing (HIP), pp 99–106

  113. Lim T, Alexander P (1995) The Dead Sea Scrolls Electronic Library, vol 1. Brill Publishers

  114. Ling H, Soatto S, Ramanathan N, Jacobs D (2007) A study of face recognition as people age. IEEE International Conference on Computer Vision (ICCV), pp 1–7. https://doi.org/10.1109/ICCV.2007.4409069

  115. Llidó D M, Llavori RB, Cabo MJA Mayr H C, Lazansk’y J, Quirchmayr G, Vogel P (eds) (2001) Extracting temporal references to assign document event-time periods, vol 2113. Springer, Heidelberg

  116. Lucarelli F, Mando PA (1996) Recent applications to the study of ancient inks with the Florence external-PIXE facility. Nucl Instr Meth Phys Res B 109-110:644–652

    Article  Google Scholar 

  117. Mani I, Wilson G (2000) Robust temporal processing of news. In: ACL 2000: Proceedings of the 38th Annual Meeting on Association for Computational Linguistics

  118. McCrone WC (1976) Authenticity of medieval document, tested by small particle analysis. Anal Chem 48(8):676A–679A

  119. McCrone WC (1988) The vinland map. Anal Chem 60:1009–1018. https://doi.org/10.1021/ac00161a013

    Article  Google Scholar 

  120. Melessanaki K, Papadakis V, Balas C, Anglos D (2001) Laser induced breakdown spectroscopy and hyper-spectral imaging analysis of pigments on an illuminated manuscript. Spectrochim Acta B 56:2337–2346

    Article  Google Scholar 

  121. Metzger BM (1981) Manuscripts of the greek bible: an introduction to greek paleography. Oxford University Press, Inc., pp 14

  122. Moalla I, LeBourgeois F, Emptoz H, Alimi AM (2006) Contribution to the Discrimination of the Medieval Manuscript Texts: Application in the Palaeography. In: Bunke H, Spitz AL (eds) Document Analysis Systems VII. DAS 2006. Lecture Notes in Computer Science, vol 3872. Springer, Berlin. https://doi.org/10.1007/11669487_3

  123. Murgue T, de la Higuera C (2004) Distances between Distributions: Comparing Language Models. In: Fred A, Caelli T.M, Duin R.P.W, Campilho A.C, de Ridder D (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2004. Lecture Notes in Computer Science, vol 3138. Springer, Berlin. https://doi.org/10.1007/978-3-540-27868-9_28

  124. National Geographic https://www.nationalgeographic.com/news/2013/5/130530-worlds-oldest-torah-scroll-bible-bologna-carbon-dating/. Accessed 23 March 2021

  125. Nesměrák K, Němcová I (2012) Dating of historical manuscripts using spectrometric methods: a Mini-Review. Anal Lett 45(4):330–344. https://doi.org/10.1080/00032719.2011.644741

    Article  Google Scholar 

  126. Oda H, Ikeda K (2010) Radiocarbon dating of kohitsugire calligraphies attributed to Fujiwara Shunzei: Akihiro-gire, Oie-gire, and Ryosa-gire. Nucl Instr Meth Phys Res B 268:1041–1044

    Article  Google Scholar 

  127. Olin JS (2003) Evidence that the vinland map is medieval. Anal Chem 75(23):6745–6747. https://doi.org/10.1021/ac034533c

  128. Orsini PO, Clarysse W (2012) Early New Testament Manuscripts and their Dates. Ephemer Theol Lovan 88(4):443–474. https://doi.org/10.2143/ETL.88.4.2957937

    Google Scholar 

  129. Pan SJ, Yang Q (2010) A survey on transfer learning. IEEE Trans Knowl Data Eng 22(10):1345–1359

    Article  Google Scholar 

  130. Ponte J, Croft W (1998) A language modelling approach to information retrieval. In: Proceedings of the 21st ACM Conference on Research and Development in Information Retrieval, pp 275–281. https://doi.org/10.1145/290941.291008

  131. Popovic M (2016) The Ancient library of Qumran between Urban and Rural Culture. In: The Dead Sea Scrolls at Qumran and the Concept of a Library. BRILL, pp 155–167

  132. Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. https://doi.org/10.1109/5.18626, vol 77, pp 257–286

  133. Renger K, Burmester A (1985/1986) The Munich Rembrandt forgeries reconsidered: A new technical approach to the investigation of drawings. Master Draw 23/24:526–537

  134. Rasmussen KL, Van der Plicht J, Doudna JG, Nielsen F, Hojrup P, Stenby EH, Petersen CT (2009) The effects of possible contamination on the radiocarbon dating of the Dead Sea Scrolls II: Empirical methods to remove castor oil and suggestions for redating. Radiocarbon 51:1005–1022

    Article  Google Scholar 

  135. Rehbein M, Sahle P, Schaßan T (2009) Codicology and Palaeography in the Digital Age. Books on Demand GmbH, Norderstedt, pp 219–235

  136. Rehman A, Naz S, Razzak MI, Hameed IA (2019) Automatic visual features for writer identification: a deep learning approach. IEEE Access 7:17149–17157

    Article  Google Scholar 

  137. Rugg G (2004) An elegant hoax? A possible solution to the Voynich Manuscript. Cryptologia 28:1:31–46. https://doi.org/10.1080/0161-110491892755

    Article  Google Scholar 

  138. Sanders HA (1935) A Third-Century Papyrus Codex of the Epistles of Paul. (Ann Arbor 1935), pp 13–15

  139. Sarlin P (2013) Self-organizing time map: an abstraction of temporal multivariate patterns. Neurocomputing 99:496–508

    Article  Google Scholar 

  140. Sawant MM, Bhurchandi K (2019) Hierarchical facial age estimation using gaussian process regression. IEEE Access 7:9142–9152. https://doi.org/10.1109/ACCESS.2018.2889873

    Article  Google Scholar 

  141. Schmeh K (2013) A milestone in voynich manuscript research: Voynich 100 conference in monte porzio catone, italy. Cryptologia 37:3:193–203. https://doi.org/10.1080/01611194.2013.797045

    Article  Google Scholar 

  142. Schniedewind WM (2005) Problems of paleographic dating of inscriptions. In: Levy T, Higham T (eds) The bible and radiocarbon dating: Archaeology. Text and Science, Routledge

  143. Settle FA (1997) Handbook of instrumental techniques for analytical chemistry. Prentice Hall PTR, Upper Saddle River, pp NJ07458

  144. Shor P (2014) The Leon Levy Dead Sea Scrolls digital library: the digitization project of the Dead Sea Scrolls. J Eastern Mediterranean Archaeol Heritage Stud 2(2):71–89

    Article  Google Scholar 

  145. Siddiqi I, Vincent N (2010) Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features. Pattern Recognit 43(11):3853–3865

    Article  MATH  Google Scholar 

  146. Song F, Croft WB (1999) A general language model for information retrieval. Proceedings of the eighth international conference on Information and knowledge management, pp 316–321

  147. Studer L, Alberti M, Pondenkandath V, Goktepe P, Kolonko T, Fischer A, Liwicki M, Ingold R (2019) A comprehensive study of imagenet pre-training for historical document image analysis. International Conference on Document Analysis and Recognition (ICDAR), pp 720–725

  148. Stutzmann D (2016) Clustering of medieval scripts through computer image analysis: towards an evaluation protocol. Digit Medievalist J 10. https://doi.org/10.16995/dm.61

  149. Sulaiman A, Omar K, Nasrudin MF, Arram A (2019) Length independent writer identification based on the fusion of deep and Hand-Crafted descriptors. IEEE Access 7:91772–91784. https://doi.org/10.1109/ACCESS.2019.2927286

    Article  Google Scholar 

  150. Svenskt Diplomatariums huvudkartotek (SDHK), https://sok.riksarkivet.se/SDHK, last accessed 20 March, 2021

  151. Szegedy C, Ioffe S, Vanhoucke V, Alemi AA (2017) Inception-v4, inception-resnet and the impact of residual connections on learning. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, pp 4278–4284

  152. Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2015) Going deeper with convolutions. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1–9. https://doi.org/10.1109/CVPR.2015.7298594

  153. Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2818–2826. https://doi.org/10.1109/CVPR.2016.308

  154. Tensmeyer C, Saunders D, Martinez T (2017) Convolutional neural networks for font classification. In: 14Th IAPR international conference on document analysis and recognition (ICDAR), vol 1, pp 985–990

  155. Thiede CP (1995) Papyrus magdalen greek 17 (Gregory-Aland p64): a reappraisal. Tyndale Bullet 46:29–42

    Google Scholar 

  156. Tigchelaar E (2010) Dead Sea Scrolls. In: The Eerdmans Dictionary of Early Judaism. Eerdmans, pp 163–180

  157. Tilahun G, Feuerverger A, Gervers M (2012) Dating mediaval english charters. Ann Appl Sci 6(4):1615–1640

    MATH  Google Scholar 

  158. Towe KM (1990) The vinland map: Still a forgery. Acc Chem Res 23:84–87. https://doi.org/10.1021/ar00171a005

    Article  Google Scholar 

  159. Trafela T, Strlic M, Kolar J, Lichtblau DA, Anders M, Mencigar DP, Pihlar B (2007) Nondestructive analysis and dating of historical paper based on IR spectroscopy and chemometric data evaluation. Anal Chem 79:6319–6323

    Article  Google Scholar 

  160. Tuniz C, Bird JR, Fink D, Herzog GF (1998) Accelerator mass spectrometry: Ultasensitive analysis for global science. CRC Press, Boca Raton

    Google Scholar 

  161. Vincent L (2007) Google book search: document understanding on a massive scale. In: International conference on document analysis and recognition (ICDAR), vol 2, pp 819–823

  162. Wahlberg F, Martensson L, Brun A (2015) Large scale style-based dating of medieval manuscripts. In: Workshop on Historical Document Image and Processing (HIP), pp 107–114. https://doi.org/10.1145/2809544.2809560

  163. Wahlberg F, Martensson L, Brun A (2016a) Historical Manuscript Production Date Estimation using Deep Convolutional Neural Networks. 15th International Conference on Frontiers in Handwriting Recognition, pp 205–210. https://doi.org/10.1109/ICFHR.2016.0048

  164. Wahlberg F, Martensson L, Brun A (2016b) Large scale continuous dating of medieval scribes using a combined image and language model. 12th IAPR Workshop on Document Analysis Systems, pp 48–53. https://doi.org/10.1109/DAS.2016.71

  165. Wang X, Feng B, Bai X, Liu W, Latecki LJ (2014) Bag of contour fragments for robust shape classification. Pattern Recogn 47(6):2116–2125

    Article  Google Scholar 

  166. Weiss K, Khoshgoftaar TM, Wang D (2016) A survey of transfer learning. J Big Data 3:9. https://doi.org/10.1186/s40537-016-0043-6

    Article  Google Scholar 

  167. Witten IH, Bell TC (1991) The zero-frequency problem: estimating the probabilities of novel events in adaptive text compression. IEEE Trans Inf Theory 37:1085–1094

  168. Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y (2009) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210–227. https://doi.org/10.1109/TPAMI.2008.79

    Article  Google Scholar 

  169. Yao H, Zhang S, Hong R, Zhang Y, Xu C, Tian Q (2019) Deep representation learning with part loss for person re-identification. IEEE Trans Image Process 28(6):2860–2871

    Article  MathSciNet  MATH  Google Scholar 

  170. Zhai C, Lafferty J (2004) A study of smoothing methods for language models applied to information retrieval. ACM Trans Inf Syst (TOIS) 22:179–214

    Article  Google Scholar 

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Electronics & Communication Engineering Department, Delhi Technological University, Delhi, India

    Enock Osoro Omayio, Sreedevi Indu & Jeebananda Panda

Authors
  1. Enock Osoro Omayio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sreedevi Indu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jeebananda Panda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Enock Osoro Omayio.

Ethics declarations

Conflict of Interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Omayio, E.O., Indu, S. & Panda, J. Historical manuscript dating: traditional and current trends. Multimed Tools Appl 81, 31573–31602 (2022). https://doi.org/10.1007/s11042-022-12927-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-12927-8

Keywords

Search

Navigation