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The Study of Three-Dimensional Fingerprint Recognition in Cultural Heritage: Trends and Challenges

Published: 16 July 2021 Publication History

Abstract

Fingerprints play a central role in any field where person identification is required. In forensics and biometrics, three-dimensional fingerprint-based imaging technologies, and corresponding recognition methods, have been vastly investigated. In cultural heritage, preliminary studies provide evidence that the three-dimensional impressions left on objects from the past (ancient fingerprints) are of paramount relevance to understand the socio-cultural systems of former societies, to possibly identify a single producer of multiple potteries, and to authenticate the artist of a sculpture. These findings suggest that the study of ancient fingerprints can be further investigated and open new avenues of research. However, the potential for capturing and analyzing ancient fingerprints is still largely unexplored in the context of cultural heritage research. In fact, most of the existing studies have focused on plane fingerprint representations and commercial software for image processing. Our aim is to outline the opportunities and challenges of digital fingerprint recognition in answering a range of questions in cultural heritage research. Therefore, we summarize the fingerprint-based imaging technologies, reconstruction methods, and analyses used in biometrics that could be beneficial to the study of ancient fingerprints in cultural heritage. In addition, we analyze the works conducted on ancient fingerprints from potteries and ceramic/fired clay sculptures. We conclude with a discussion on the open challenges and future works that could initiate novel strategies for ancient fingerprint acquisition, digitization, and processing within the cultural heritage community.

References

[1]
Irene Aicardi, Filiberto Chiabrando, Andrea Maria Lingua, and Francesca Noardo. 2018. Recent trends in cultural heritage 3D survey: The photogrammetric computer vision approach. Journal of Cultural Heritage 32 (2018), 257–266.
[2]
M. O. Altan, T. M. Celikoyan, G. Kemper, and G. Toz. 2004. Balloon photogrammetry for cultural heritage. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 35, B5 (2004), 964–968.
[3]
Mafkereseb Kassahun Bekele, Roberto Pierdicca, Emanuele Frontoni, Eva Savina Malinverni, and James Gain. 2018. A survey of augmented, virtual, and mixed reality for cultural heritage. ACM Journal on Computing and Cultural Heritage 11, 2 (2018), 1–36.
[4]
Lucy E. Bennison-Chapman and Lori D. Hager. 2018. Tracking the division of labour through handprints: Applying Reflectance Transformation Imaging (RTI) to clay ‘tokens’ in Neolithic West Asia. Journal of Archaeological Science 99 (2018), 112–123.
[5]
Fabio Bettio, Ruggero Pintus, Alberto Jaspe Villanueva, Emilio Merella, Fabio Marton, and Enrico Gobbetti. 2015. Mont’e scan: Effective shape and color digitization of cluttered 3D artworks. ACM Journal on Computing and Cultural Heritage 8, 1 (2015), 1–23.
[6]
Gabriele Bitelli, Beatrice Borghi, Chiara Francolini, and Filippo Galletti. 2020. New hypotheses and interpretations regarding the Longobard Basin in the “Jerusalem” of Bologna supported by 3D surveying methodologies. Journal of Cultural Heritage 46 (2020), 226–234.
[7]
Franco Casali. 2006. X-ray and neutron digital radiography and computed tomography for cultural heritage. Physical Techniques in the Study of Art, Archaeology and Cultural Heritage 1 (2006), 41–123.
[8]
Paolo Castellini, Enrico Esposito, Barbara Marchetti, Nicola Paone, and Enrico P. Tomasini. 2003. New applications of scanning laser doppler vibrometry (SLDV) to non-destructive diagnostics of artworks: Mosaics, ceramics, inlaid wood and easel painting. Journal of Cultural Heritage 4 (2003), 321–329.
[9]
Kuo-En Chang, Chia-Tzu Chang, Huei-Tse Hou, Yao-Ting Sung, Huei-Lin Chao, and Cheng-Ming Lee. 2014. Development and behavioral pattern analysis of a mobile guide system with augmented reality for painting appreciation instruction in an art museum. Computers & Education 71 (2014), 185–197.
[10]
Tarang Chugh and Anil K. Jain. 2019. OCT fingerprints: Resilience to presentation attacks. arXiv:1908.00102.
[11]
Sophia Bethany Coban, Felix Lucka, Willem Jan Palenstijn, Denis Van Loo, and Kees Joost Batenburg. 2020. Explorative imaging and its implementation at the flex-ray laboratory. Journal of Imaging 6, 4 (2020), 18.
[12]
Luke Nicholas Darlow and Benjamin Rosman. 2017. Fingerprint minutiae extraction using deep learning. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB’17). IEEE, Los Alamitos, CA, 22–30.
[13]
T. J. David. 1981. Distribution, age and sex variation of the mean epidermal ridge breadth. Human Heredity 31, 5 (1981), 279–282.
[14]
Marta Dominguez-Delmas. 2020. Seeing the forest for the trees: New approaches and challenges for dendroarchaeology in the 21st century. Dendrochronologia 62 (2020), 125731.
[15]
Raffaella Fontana, Maria Chiara Gambino, Marinella Greco, Enrico Pampaloni, Luca Pezzati, and Roberto Scopigno. 2003. High-resolution 3D digital models of artworks. In Optical Metrology for Arts and Multimedia, Vol. 5146. International Society for Optics and Photonics, 34–43.
[16]
Kent D. Fowler, Jon Ross, Elizabeth Walker, Christian Barritt-Cleary, Haskel J. Greenfield, and Aren M. Maeir. 2020. Fingerprint evidence for the division of labour and learning pottery-making at early bronze age tell es-Sâfi/Gath, israel. PLoS One 15, 4 (2020), e0231046.
[17]
Kent D. Fowler, Elizabeth Walker, Haskel J. Greenfield, Jon Ross, and Aren M. Maeir. 2019. The identity of potters in early states: Determining the age and sex of fingerprints on early bronze age pottery from tell es-Sâfi/Gath, Israel. Journal of Archaeological Method and Theory 26, 4 (2019), 1470–1512.
[18]
Peter Fried, Jonathan Woodward, David Brown, Drew Harvell, and James Hanken. 2020. 3D scanning of antique glass by combining photography and computed tomography. Digital Applications in Archaeology and Cultural Heritage (2020), e00147.
[19]
Hartwig Fronthaler, Klaus Kollreider, and Josef Bigun. 2008. Local features for enhancement and minutiae extraction in fingerprints. IEEE Transactions on Image Processing 17, 3 (2008), 354–363.
[20]
Javier Galbally, Laurent Beslay, and Gunnar Böstrom. 2020. 3D-FLARE: A touchless full-3D fingerprint recognition system based on laser sensing. IEEE Access 8 (2020), 145513–145534.
[21]
Carsten Gottschlich. 2011. Curved-region-based ridge frequency estimation and curved Gabor filters for fingerprint image enhancement. IEEE Transactions on Image Processing 21, 4 (2011), 2220–2227.
[22]
Kan Guo, Dongqing Zou, and Xiaowu Chen. 2015. 3d mesh labeling via deep convolutional neural networks. ACM Transactions on Graphics 35, 1 (2015), 1–12.
[23]
Esperanza Gutiérrez-Redomero, Ángeles Sánchez-Andrés, Noemí Rivaldería, Concepción Alonso-Rodríguez, José E. Dipierri, and Luis M. Martín. 2013. A comparative study of topological and sex differences in fingerprint ridge density in Argentinian and Spanish population samples. Journal of Forensic and Legal Medicine 20, 5 (2013), 419–429.
[24]
Megan Hancock. 2015. Museums and 3D printing: More than a workshop novelty, connecting to collections and the classroom. Bulletin of the Association for Information Science and Technology 42, 1 (2015), 32–35.
[25]
Yvonne Y. W. Ho, David M. Evans, Grant W. Montgomery, Anjali K. Henders, John P. Kemp, Nicholas J. Timpson, Beate St. Pourcain, et al. 2016. Genetic variant influence on whorls in fingerprint patterns. Journal of Investigative Dermatology 136, 4 (2016), 859.
[26]
Lin Hong, Yifei Wan, and Anil Jain. 1998. Fingerprint image enhancement: Algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 8 (1998), 777–789.
[27]
Lu Jiang, Tong Zhao, Chaochao Bai, A. Yong, and Min Wu. 2016. A direct fingerprint minutiae extraction approach based on convolutional neural networks. In Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN’16). IEEE, Los Alamitos, CA, 571–578.
[28]
Xiaoyue Jiang, Yipeng Lu, Hao-Yen Tang, Julius M. Tsai, Eldwin J. Ng, Michael J. Daneman, Bernhard E. Boser, and David A. Horsley. 2017. Monolithic ultrasound fingerprint sensor. Microsystems & Nanoengineering 3, 1 (2017), 1–8.
[29]
Suksan Jirachaweng, Zujun Hou, Wei-Yun Yau, and Vutipong Areekul. 2011. Residual orientation modeling for fingerprint enhancement and singular point detection. Pattern Recognition 44, 2 (2011), 431–442.
[30]
Kathryn A. Kamp, Nichole Timmerman, Gregg Lind, Jules Graybill, and Ian Natowsky. 1999. Discovering childhood: Using fingerprints to find children in the archaeological record. American Antiquity 64, 2 (1999), 309–315.
[31]
Vivek Kanhangad, Ajay Kumar, and David Zhang. 2011. A unified framework for contactless hand verification. IEEE Transactions on Information Forensics and Security 6, 3 (2011), 1014–1027.
[32]
John Kantner, David McKinney, Michele Pierson, and Shaza Wester. 2019. Reconstructing sexual divisions of labor from fingerprints on ancestral Puebloan pottery. Proceedings of the National Academy of Sciences 116, 25 (2019), 12220–12225.
[33]
Miroslav Králík and Ladislav Nejman. 2007. Fingerprints on artifacts and historical items: Examples and comments. Journal of Ancient Fingerprints 1, 1 (2007), 4–13.
[34]
Miroslav Králík and Vladimir Novotný. 2003. Epidermal ridge breadth: An indicator of age and sex in paleodermatoglyphics. Variability and Evolution 11, 2003 (2003), 5–30.
[35]
Kewal Krishan, Tanuj Kanchan, and Chitrabala Ngangom. 2013. A study of sex differences in fingerprint ridge density in a North Indian young adult population. Journal of Forensic and Legal Medicine 20, 4 (2013), 217–222.
[36]
Ajay Kumar. 2018. Contactless 3D Fingerprint Identification. Springer.
[37]
Ajay Kumar and Cyril Kwong. 2013. Towards contactless, low-cost and accurate 3D fingerprint identification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3438–3443.
[38]
Ruggero Donida Labati, Angelo Genovese, Vincenzo Piuri, and Fabio Scotti. 2012. Two-view contactless fingerprint acquisition systems: A case study for clay artworks. In Proceedings of the 2012 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS’12). IEEE, Los Alamitos, CA, 1–8.
[39]
R. Donida Labati, Angelo Genovese, Vincenzo Piuri, and Fabio Scotti. 2014. Touchless fingerprint biometrics: A survey on 2D and 3D technologies. Journal of Internet Technology 15, 3 (2014), 325–332.
[40]
Ruggero Donida Labati, Angelo Genovese, Vincenzo Piuri, and Fabio Scotti. 2015. Toward unconstrained fingerprint recognition: A fully touchless 3-D system based on two views on the move. IEEE Transactions on Systems, Man, and Cybernetics: Systems 46, 2 (2015), 202–219.
[41]
Ngoc Tuyen Le, Jing-Wein Wang, Duc Huy Le, Chih-Chiang Wang, and Tu N. Nguyen. 2020. Fingerprint enhancement based on tensor of wavelet subbands for classification. IEEE Access 8 (2020), 6602–6615.
[42]
Jiajia Lei, Hiyam Hatem, Long Zhou, Xinge You, Patrick S. P. Wang, and Duanquan Xu. 2010. Fingerprint enhancement based on non-separable wavelet. In Proceedings of the 9th IEEE International Conference on Cognitive Informatics (ICCI’10). IEEE, Los Alamitos, CA, 313–317.
[43]
Jian Li, Jianjiang Feng, and C.-C. Jay Kuo. 2018. Deep convolutional neural network for latent fingerprint enhancement. Signal Processing: Image Communication 60 (2018), 52–63.
[44]
Achim Lichtenberger and Kimberlee S. Moran. 2018. Ancient fingerprints from Beit Nattif: Studying Late Roman clay impressions on oil lamps and figurines. Antiquity 92, 361 (2018), e3.
[45]
Chenhao Lin and Ajay Kumar. 2017. Tetrahedron based fast 3D fingerprint identification using colored LEDs illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 12 (2017), 3022–3033.
[46]
Chenhao Lin and Ajay Kumar. 2018. Contactless and partial 3D fingerprint recognition using multi-view deep representation. Pattern Recognition 83 (2018), 314–327.
[47]
Feng Liu, Jinrong Liang, Linlin Shen, Meng Yang, David Zhang, and Zhihui Lai. 2017. Case study of 3D fingerprints applications. PLoS One 12, 4 (2017), e0175261.
[48]
Feng Liu, Guojie Liu, Qijun Zhao, and Linlin Shen. 2020. Robust and high-security fingerprint recognition system using optical coherence tomography. Neurocomputing 402 (2020), 14–28.
[49]
Feng Liu and David Zhang. 2014. 3D fingerprint reconstruction system using feature correspondences and prior estimated finger model. Pattern Recognition 47, 1 (2014), 178–193.
[50]
Feng Liu, Yuanhao Zhao, Guojie Liu, and Linlin Shen. 2020. Fingerprint pore matching using deep features. Pattern Recognition 102 (2020), 107208.
[51]
Feng Zhao Liu, Qijun Zhao, and David Zhang. 2020. Advanced Fingerprint Recognition: From 3D Shape to Ridge Detail. Springer.
[52]
Nancy Lloyd. 1999. Fingerprints. Gaskell and Lie, Sketches in Clay 119 (1999), 24.
[53]
Yipeng Lu, H. Tang, Stephanie Fung, Qi Wang, J. M. Tsai, M. Daneman, B. E. Boser, and D. A. Horsley. 2015. Ultrasonic fingerprint sensor using a piezoelectric micromachined ultrasonic transducer array integrated with complementary metal oxide semiconductor electronics. Applied Physics Letters 106, 26 (2015), 263503.
[54]
João Felipe Machado, Paula Roquetti Fernandes, Ricardo Wagner Roquetti, and José Fernandes Filho. 2010. Digital dermatoglyphic heritability differences as evidenced by a female twin study. Twin Research and Human Genetics 13, 5 (2010), 482–489.
[55]
Dario Maio, Davide Maltoni, Raffaele Cappelli, James L. Wayman, and Anil K. Jain. 2002. FVC2002: Second fingerprint verification competition. In Object Recognition Supported by User Interaction for Service Robots, Vol. 3. IEEE, Los Alamitos, CA, 811–814.
[56]
Davide Maltoni, Dario Maio, Anil K. Jain, and Salil Prabhakar. 2009. Handbook of Fingerprint Recognition. Springer Science & Business Media.
[57]
Adam Metallo and Vince Rossi. 2011. The future of three-dimensional imaging and museum applications. Curator: The Museum Journal 54, 1 (2011), 63–69.
[58]
M. P. Morigi, F. Casali, M. Bettuzzi, R. Brancaccio, and V. D’Errico. 2010. Application of X-ray computed tomography to cultural heritage diagnostics. Applied Physics A 100, 3 (2010), 653–661.
[59]
Amy Z. Mundorff, Eric J. Bartelink, and Turhon A. Murad. 2014. Sexual dimorphism in finger ridge breadth measurements: A tool for sex estimation from fingerprints. Journal of Forensic Sciences 59, 4 (2014), 891–897.
[60]
Dinh-Luan Nguyen, Kai Cao, and Anil K. Jain. 2018. Robust minutiae extractor: Integrating deep networks and fingerprint domain knowledge. In Proceedings of the 2018 International Conference on Biometrics (ICB’18). IEEE, Los Alamitos, CA, 9–16.
[61]
PAN. n.d. Portable Antiquities of the Netherlands. Retrieved June 11, 2021 from www.portable-antiquities.nl.
[62]
Karen Panetta, Srijith Rajeev, K. M. Shreyas Kamath, and Sos S. Agaian. 2019. Unrolling post-mortem 3D fingerprints using mosaicking pressure simulation technique. IEEE Access 7 (2019), 88174–88185.
[63]
Geppy Parziale, Eva Diaz-Santana, and Rudolf Hauke. 2006. The Surround Imager™: A multi-camera touchless device to acquire 3D rolled-equivalent fingerprints. In Proceedings of the International Conference on Biometrics. 244–250.
[64]
Lica Pezzati and Raffaella Fontana. 2008. 3D scanning of artworks. In Handbook on the Use of Laser in Conservation and Conservation Science.COST Office, Brussels, Belgium.
[65]
P. Jonathon Phillips, J. Ross Beveridge, Bruce A. Draper, Geof Givens, Alice J. O’Toole, David Bolme, Joseph Dunlop, Yui Man Lui, Hassan Sahibzada, and Samuel Weimer. 2012. The good, the bad, and the ugly face challenge problem. Image and Vision Computing 30, 3 (2012), 177–185.
[66]
Roberto Pierdicca, Emanuele Frontoni, Eva Savina Malinverni, Francesca Colosi, and Roberto Orazi. 2016. Virtual reconstruction of archaeological heritage using a combination of photogrammetric techniques: Huaca Arco Iris, Chan Chan, Peru. Digital Applications in Archaeology and Cultural Heritage 3, 3 (2016), 80–90.
[67]
Charles R. Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas J. Guibas. 2016. Volumetric and multi-view CNNs for object classification on 3D data. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 5648–5656.
[68]
Nalini Ratha and Ruud Bolle. 2003. Automatic Fingerprint Recognition Systems. Springer Science & Business Media.
[69]
Stephen G. Rees-Jones. 1978. A fifteenth century Florentine terracotta relief: Technology, conservation, interpretation. Studies in Conservation 23, 3 (1978), 95–112.
[70]
Roberto Ricci, Roberta Fantoni, Mario Ferri de Collibus, Giorgio G. Fornetti, Massimiliano Guarneri, and Claudio Poggi. 2003. High-resolution laser radar for 3D imaging in artwork cataloging, reproduction, and restoration. In Optical Metrology for Arts and Multimedia, Vol. 5146. International Society for Optics and Photonics, 62–73.
[71]
Sunita Saha, Piotr Foryś, Jacek Martusewicz, and Robert Sitnik. 2020. Approach to analysis the surface geometry change in cultural heritage objects. In Proceedings of the International Conference on Image and Signal Processing. Springer, 3–13.
[72]
Akiva Sanders. 2015. Fingerprints, sex, state, and the organization of the Tell Leilan ceramic industry. Journal of Archaeological Science 57 (2015), 223–238.
[73]
Inga Siebke, Lorenzo Campana, Marianne Ramstein, Anja FurtwAngler, Albert Hafner, and Sandra Losch. 2018. The application of different 3D-scan-systems and photogrammetry at an excavation—A Neolithic dolmen from Switzerland. Digital Applications in Archaeology and Cultural Heritage 10 (2018), e00078.
[74]
Susan L. Stinson. 2004. Household Ritual, Gender, and Figurines in the Hohokam Regional System. Master’s Thesis. University of Arizona.
[75]
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik Learned-Miller. 2015. Multi-view convolutional neural networks for 3D shape recognition. In Proceedings of the IEEE International Conference on Computer Vision. 945–953.
[76]
Jan Svoboda, Federico Monti, and Michael M. Bronstein. 2017. Generative convolutional networks for latent fingerprint reconstruction. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB’17). IEEE, Los Alamitos, CA, 429–436.
[77]
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015. Going deeper with convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1–9.
[78]
Hanzhuo Tan and Ajay Kumar. 2020. Towards more accurate contactless fingerprint minutiae extraction and pose-invariant matching. IEEE Transactions on Information Forensics and Security 15 (2020), 3924–3937.
[79]
Yao Tang, Fei Gao, and Jufu Feng. 2017. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB’17). IEEE, Los Alamitos, CA, 117–123.
[80]
Yao Tang, Fei Gao, Jufu Feng, and Yuhang Liu. 2017. FingerNet: An unified deep network for fingerprint minutiae extraction. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics (IJCB’17). IEEE, Los Alamitos, CA, 108–116.
[81]
Nanne Van Noord and Eric Postma. 2017. Learning scale-variant and scale-invariant features for deep image classification. Pattern Recognition 61 (2017), 583–592.
[82]
Marilena Vecco. 2010. A definition of cultural heritage: From the tangible to the intangible. Journal of Cultural Heritage 11, 3 (2010), 321–324.
[83]
Carol Vogel. 2014. Recreating Adam, from hundreds of fragments, after the fall. New York Times. Retrieved June 11, 2021 from https://www.nytimes.com/2014/11/09/arts/design/recreating-adam-from-hundreds-of-fragments-after-the-fall.html.
[84]
Guo Chun Wan, Meng Meng Li, He Xu, Wen Hao Kang, Jin Wen Rui, and Mei Song Tong. 2020. XFinger-Net: Pixel-wise segmentation method for partially defective fingerprint based on attention gates and U-Net. Sensors 20, 16 (2020), 4473.
[85]
Haixia Wang, Xicheng Yang, Peng Chen, Baojin Ding, Ronghua Liang, and Yipeng Liu. 2020. Acquisition and extraction of surface and internal fingerprints from optical coherence tomography through 3D fully convolutional network. Optik 205 (2020), 164176.
[86]
Wei Wang, Jianwei Li, Feifei Huang, and Hailiang Feng. 2008. Design and implementation of log-Gabor filter in fingerprint image enhancement. Pattern Recognition Letters 29, 3 (2008), 301–308.
[87]
Yongchang Wang, Laurence G. Hassebrook, and Daniel L. Lau. 2010. Data acquisition and processing of 3-D fingerprints. IEEE Transactions on Information Forensics and Security 5, 4 (2010), 750–760.
[88]
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao. 2015. 3D ShapeNets: A deep representation for volumetric shapes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1912–1920.
[89]
Wuyuan Xie, Zhan Song, and Ronald C. Chung. 2013. Real-time three-dimensional fingerprint acquisition via a new photometric stereo means. Optical Engineering 52, 10 (2013), 103103.
[90]
Yuanrong Xu, Guangming Lu, Yao Lu, and David Zhang. 2019. High resolution fingerprint recognition using pore and edge descriptors. Pattern Recognition Letters 125 (2019), 773–779.
[91]
Ying Xu, Yi Wang, Jiajun Liang, and Yong Jiang. 2020. Augmentation data synthesis via GANs: Boosting latent fingerprint reconstruction. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’20). IEEE, Los Alamitos, CA, 2932–2936.
[92]
Naci Yastikli. 2007. Documentation of cultural heritage using digital photogrammetry and laser scanning. Journal of Cultural Heritage 8, 4 (2007), 423–427.
[93]
Sergey Zagoruyko and Nikos Komodakis. 2015. Learning to compare image patches via convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4353–4361.
[94]
Wuchen Zhang, Deborah A. Kosiorek, and Amy N. Brodeur. 2020. Application of structured-light 3-D scanning to the documentation of plastic fingerprint impressions: A quality comparison with traditional photography. Journal of Forensic Sciences 65, 3 (2020), 784–790.

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    cover image Journal on Computing and Cultural Heritage
    Journal on Computing and Cultural Heritage   Volume 14, Issue 4
    December 2021
    328 pages
    ISSN:1556-4673
    EISSN:1556-4711
    DOI:10.1145/3476246
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    Publication History

    Published: 16 July 2021
    Accepted: 01 April 2021
    Revised: 01 April 2021
    Received: 01 December 2020
    Published in JOCCH Volume 14, Issue 4

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    Author Tags

    1. Ancient fingerprints
    2. fired clay sculptures
    3. heritage biometrics
    4. pottery

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