Implementation of Total Variation algorithm for better interpretation of radiography images of Tavichi family historic hats - Journal of Research on Archaeometry
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year 8, Issue 1 (2022)                   JRA 2022, 8(1): 83-95 | Back to browse issues page

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Pazira F, Yahaghi E, Movafeghi A, Madrid Garcia J A. Implementation of Total Variation algorithm for better interpretation of radiography images of Tavichi family historic hats. JRA 2022; 8 (1) :83-95
1- Department of Physics, Faculty of Science, Imam Khomeini International University, Qazvin, Iran
2- Department of Physics, Faculty of Science, Imam Khomeini International University, Qazvin, Iran ,
3- Reactor and Nuclear Safety Research School, Nuclear Science and Technology Research Institute, Tehran, Iran
4- Department of Conservation and Restoration of Cultural Heritage, Valencia Polytechnic University, Valencia, Spain
Abstract:   (337 Views)
Hats are used to protect the head and for safety or fashion in different cultures and nations. Identifying the fabric, designs, and sewing the hat can give us good information about the history of fashion in different nations. In this study, five hats belonging to the Tavichi family in Italy were investigated by radiography. The design and construction, morphology, internal structure and damaged regions have been considered. Image processing algorithms can increase the quality of radiography images. In this research, total variation (TV) and shape from shading (SFS) algorithms have been used to enhance the quality of the images. The TV method is based on minimizing the changes and is used to eliminate noise in images. In the 3D method, a 3D image is created from a 2D image based on the light reflected. The results show that radiography testing is an effective method for identifying the structure of old hats and can show the internal structure and connections of the components without splitting the fabric. The processed images also have better contrast and can be used to identify components and structures. The radiography and restoration experts have evaluated the reconstructed images. They have confirmed the effectiveness of processing methods in extracting efficient information from radiographs. Also, the profile lines of the images show that the contrast changes in the reconstructed images are greater than the original radiographs, and the components of the reconstructed images are clearer.
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Technical Note: Original Research | Subject: Conservation Science
Received: 2022/04/22 | Accepted: 2022/07/16 | Published: 2022/08/21 | ePublished: 2022/08/21

1. Range dost sh., History of Iranian clothing, Jamal Honarzban Institute, 2009 [In Persian] [رنج‌دوست ش. تاریخ لباس ایران، موسسه جمال هنرزبان، 1388.]
2. Tortora Ph. G., Eubank K., Survey of Historic Costume: A History Of Western Dress, Fairchild Pubns; 5th edition, 2010.
3. Kevin L, Chengyu S, Yuan Z, Yanping L. Structural Analysis of Three-Dimensional Mesh Fabric by Micro X-ray computed tomography. J. Eng. fibers and fabrics. December 2019.
4. Anita Q. Factors Influencing the Stability of Man-made Fibers: A Retrospective View for Historical Textiles. J. Poly. Degradation and Stability. September 2014, 210-218. [DOI:10.1016/j.polymdegradstab.2014.03.002]
5. Dawei L, Wei W, Feng T, Wei L, Christophe J. The Oldest Bark Cloth Beater in Southern China (Dingmo, Bubing basin, Guangxi). J. Quaternary Int. 2014, 184-189. [DOI:10.1016/j.quaint.2014.06.062]
6. Eckart K, Benjamin S, Tony W, Michal M, Robert B, Maik G. Forming Analysis of Internal Plies of Multi-Layer Unidirectional Textile Preforms Using Projectional Radiography. J. pricedia manufacturing. April 2020; 17-23. [DOI:10.1016/j.promfg.2020.04.110]
7. Martin H, Tomas T, Radek P, Vladimir L. Mediaeval Metal Threads and Their Identification Using Micro-XRF Scanning, Confocal XRF, and X-ray Micro-Radiography. J. Radiat. Phys. Chem., February 2019, 299-303. [DOI:10.1016/j.radphyschem.2018.04.016]
8. Douglas C, Andre M, Douglas K, Erika B, Digital Radiographic Image Processing and Analysis. J. Dental Clinics of North America. July 2018, 341-359. [DOI:10.1016/j.cden.2018.03.001]
9. Nour A, Harby A, Amal E, Sally E. Green and Novel Approach for Enhancing Flame Retardancy, UV Protection and Mechanical Properties of Fabrics Utilized in Historical Textile Fabrics Conservation. Prog. Org. Coat., May 2022, 106822. [DOI:10.1016/j.porgcoat.2022.106822]
10. Yazeed A, Nasser S, Abdulrahman A, Sami A, Sami B. an Assessment of Image Reject Rates for Digital Radiography in Saudi Arabia: A cross-sectional study. JRRAS, March 2022, 219-223. [DOI:10.1016/j.jrras.2022.01.023]
11. Paolo D, Massimillinao G, Daniele M, Valeria S, Alessandro D, Arianna M, Veronica P, Mauro M. Noninvasive Analyses of Low-Contrast Images on Ancient Textiles. J. Cult. Herit. January-february 2016; 14-19. [DOI:10.1016/j.culher.2015.07.008]
12. Philippe C, Christophe M, Alberto A, Thierry S, Isabelle H. Radiographic Analysis of Three Royal Effigies of Abomey (Benin). J. Forensic Imaging. December 2021, 200478. [DOI:10.1016/j.fri.2021.200478]
13. Liberato D, Cinzia G, Rocco L, Francesco S, Teresa S, Emilia M, Giulio F. X-ray Dating of Ancient Linen Fabrics. J. of MDPI. November 2019.
14. Mirzapour M, Yahaghi E, Movafeghi A. The Performance of Three Total Variation Based Algorithms for Enhancing the Contrast of Industrial Radiography Images, J. Nondestr Eval. 2021, 32:1, 10-23, DOI: 10.1080/09349847.2020.1836293. [DOI:10.1080/09349847.2020.1836293]
15. Yahaghi E., Movafeghi A., Contrast Enhancement of Industrial Radiography Images by Gabor Filtering with Automatic Noise Thresholding, Russ. J. Nondestr. Test., 2019, 55 (1), 73-79. [DOI:10.1134/S1061830919010121]
16. Yahaghi E., Using Total Variation Denoising for Detecting Defects in Industrial Radiography, Insight.,5(6), 2016-308-311.
17. Getreuer P., Rudin-Osher-Fatemi Total Variation Denoising Using Split Bregman, IPOL, 2012. [DOI:10.5201/ipol.2012.g-tvd]
18. Jiacheng F, Yuan F, Jinqiu M, Shigang W, Qinghua L. 3D Reconstruction of Non-textured Surface by Combining Shape from Shading and Stereovision. J. Meas. November 2021, 110029. [DOI:10.1016/j.measurement.2021.110029]
19. Ziyi C, Yaxiang W, Wenfeng Z, Lirong Y, Yushan T, Wang M, Shan L, Bo Y. The Algorithm of Stereo Vision and Shape From Shading Based on Endoscope Imaging. J. Bio. Signal Proc. and Control. July 2022, 103658. [DOI:10.1016/j.bspc.2022.103658]
20. Luca P, Irene C, Filippo R, Emanuele S. X-ray Shape-from-Silhouette for Three-Dimensional Modelling Applied to Ancient Metallic Handworks. J. Cult. Herit. June 2013, e169-e175. [DOI:10.1016/j.culher.2012.10.021]

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