Margrethe Havgar

• Fadillah, Riestiya Zain; Gigilashvili, Davit; Havgar, Margrethe; Vedeler, Marianne & Hardeberg, Jon Yngve (2026). Automated thread counting in archaeological textiles using pulse-based feature extraction. The European Physical Journal Plus. 141, s. 1–28. doi: 10.1140/epjp/s13360-025-07194-z. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Archaeological textiles are often highly fragmented, posing significant challenges for reconstruction and analysis. Human experts traditionally rely on technical analyses, such as thread counting, to match fragments and determine their origins. However, this process is labour-intensive and time-consuming, especially for degraded artefacts such as the Oseberg tapestry from the Viking Age. Despite the potential for automation, existing computational methods have proven insufficiently robust, lacking the nuanced approach that human expertise offers. We propose a framework for automating thread counting in textile images using a feature extractor to capture thread counts in vertical and horizontal directions. Our method models thread counting as a pulse counting problem, inspired by how humans intuitively count threads. It involves analysing traces of pixel values from binary and gradient images to estimate thread density. Our method was compared to measurements by human experts, and while it tended to overestimate thread counts, it showed promising results in clustering fragments. Specifically, 14 out of 27 fragments were grouped in alignment with archaeologists’ hypotheses regarding their origins. Our method offers a valuable tool for digitally reconstructing archaeological textiles, improving efficiency in analysing and matching fragmented artefacts. Future work will focus on refining our approach with advanced thresholding techniques, modelling complex weaving techniques and utilizing hyperspectral images to improve accuracy in identifying complex weaving structures and mixed thread materials.

• Gigilashvili, Davit; Gulbrandsen, Casper Fabian; Nguyen, Ha Thu; Havgar, Margrethe; Vedeler, Marianne & Hardeberg, Jon Yngve (2024). Toward Solving a Puzzle of Fragmented Archeological Textiles. Journal of Imaging Science and Technology. ISSN 1062-3701. 68(4), s. 1–16. doi: 10.2352/J.ImagingSci.Technol.2024.68.4.040407. Fulltekst i vitenarkiv Vis sammendrag

  Archeological textiles can provide invaluable insight into the past. However, they are often highly fragmented, and a puzzle has to be solved to re-assemble the object and recover the original motifs. Unlike common jigsaw puzzles, archeological fragments are highly damaged, and no correct solution to the puzzle is known. Although automatic puzzle solving has fascinated computer scientists for a long time, this work is one of the first attempts to apply modern machine learning solutions to archeological textile re-assembly. First and foremost, it is important to know which fragments belong to the same object. Therefore, features are extracted from digital images of textile fragments using color statistics, classical texture descriptors, and deep learning methods. These features are used to conduct clustering and identify similar fragments. Four different case studies with increasing complexity are discussed in this article: from well-preserved textiles with available ground truth to an actual open problem of Oseberg archeological tapestry with unknown solution. This work reveals significant knowledge gaps in current machine learning, which helps us to outline a future avenue toward more specialized application-specific models.

• Gigilashvili, Davit; Nguyen, Ha Thu; Gulbrandsen, Casper Fabian; Havgar, Margrethe; Vedeler, Marianne & Hardeberg, Jon Yngve (2023). Texture-based clustering of archaeological textile images. Archiving Conference. ISSN 2161-8798. s. 139–142. doi: 10.2352/issn.2168-3204.2023.20.1.29. Fulltekst i vitenarkiv Vis sammendrag

  Archaeological textiles are often highly fragmented, and solving a puzzle is needed to recover the original composition and respective motifs. The lack of ground truth and unknown number of the original artworks that the fragments come from complicate this process. We clustered the RGB images of the Viking Age Oseberg Tapestry based on their texture features. Classical texture descriptors as well as modern deep learning were used to construct a texture feature vector that was subsequently fed to the clustering algorithm. We anticipated that the clustering outcome would give indications to the number of original artworks. While the two clusters of different textures emerged, this finding needs to be taken with care due to a broad range of limitations and lessons learned.

• Karlsen, Joakim; Havgar, Margrethe & Rødsrud, Christian Løchsen (2023). ‘Always Viking’: Archaeologists Collaborating with Public Service Media to Broaden Access to Archaeological Fieldwork. Public Archaeology. ISSN 1465-5187. s. 1–23. doi: 10.1080/14655187.2023.2213511. Fulltekst i vitenarkiv Vis sammendrag

  This article examines how collaboration with Public Service Media structures the relationship between archaeologists and the public. To be able to understand such collaborations, we have studied an online news production by the Norwegian Broadcasting Corporation, ‘Always Viking’, covering one week of excavating the recently discovered Viking ship at Gjellestad in Norway. The findings suggest that the journalists, even when doing an online-first production, mostly worked according to a broadcasting media logic, with few opportunities for the public to participate. In this, they prioritized the audience’s ‘perceived reality’ over the archaeologists’ ‘referential reality’ (Holtorf, Citation2007: 151–52) to secure a broader reach. Some elements of the format supported more reciprocal audience participation, however, by combining a livestream with open and ongoing Q&A sessions. This opened for more unmediated, direct, and meaningful encounters between the archaeologists and the public. Overall, the study shows that the long and mutually beneficial collaboration between public service broadcasting and archaeology (Piccini, Citation2007) can be strengthened by undertaking joint experimentation and exploration of participatory communication models online.

• Havgar, Margrethe Kirby Hopstock (2020). Sessrúmnir og seilende vindhester  Skip som konsept i førkristen, norrøn verdensforståelse. Viking - Norsk arkeologisk årbok. ISSN 0332-608X. 83(1), s. 85–95. doi: 10.5617/viking.8252. Fulltekst i vitenarkiv Vis sammendrag

  Ships appear in several, varied contexts in the Viking Age. These contexts are in this article used to discuss the ship’s connection to overall pre-Christian, Norse mentality. Kennings such as byrjar drösla (sailing wind horse) shows the ship’s connection to horses, considered as independent agents able to cross between spheres. This, in particular, is discussed in connection to Freya’s hall Sessrúmnir, a hall which also appears on a list of ships in Skaldskaparmál. Based on the analyses presented in this article, it is argued that ships were connected to a complex, inference-based framework of understanding where they had several, varied identities and roles. Interpreting burial ships, such as the Oseberg ship, simply as burial homes or death vessels might therefore severely limit our present understanding of the multifaceted nature of the ship in pre-Christian, Norse mentality.

Sjå alle arbeida i NVA

• Havgar, Margrethe & Rimstad, Emma T. (2026). International Runes. doi: https:/open.spotify.com/episode/2TOM3KCEhjM0HrPcTCuICF?si=RFb8HD7GRRGFyx--_gVvoA. Fulltekst i vitenarkiv Vis sammendrag

  In this week's episode, Dan and Mags catch up with Ema Tennås Rimstad to explore how runes have been represented in other languages.

• Havgar, Margrethe & Rimstad, Emma T. (2025). Runes Glorious Runes. doi: https:/open.spotify.com/episode/1SY8pNn7oaWfJBRNxB0AYX?si=SfbwSKrBSj6ffbpgqz01Bw. Fulltekst i vitenarkiv Vis sammendrag

  In this week's episode, Dan and Mags have a chat with Ema Tennås Rimstad. A Doctoral Fellow in Philology who has been researching the use of bind runes during the Middle Ages in Norway.

• Farrand, Daniel; Havgar, Margrethe & Dale, Roderick Thomas Duncan (2025). Nordic Mythology Podcast: Berserker and Ulfhednar with Dr Roderick Dale. doi: https:/shows.acast.com/nordicmytholoypodcast/episodes/ep-289-berserker-and-ulfhednar-with-dr-roderick-dale. Fulltekst i vitenarkiv
• Gigilashvili, Davit; George, Sony; Lukesova, Hana; Havgar, Margrethe; Vedeler, Marianne & Kutzke, Hartmut (2024). A Puzzling Problem of the Viking Age Tapestry. Fulltekst i vitenarkiv
• Fadillah, Riestiya Zain; Gigilashvili, Davit; Havgar, Margrethe; Vedeler, Marianne & Hardeberg, Jon Yngve (2024). Automatic Thread Counting for Archaeological Textiles. Fulltekst i vitenarkiv Vis sammendrag

  Archaeological textile artifacts are often fragmented and human experts need to solve a puzzle to find matching pieces and reconstruct the original. This is a challenging task due to missing or degraded fragments, deformations and fading. Often it is not even known whether fragments come from the same object or not. A good example is the Oseberg Tapestry from the Viking Age [1]. Matching is usually done by experts who rely on technical analysis of the textile. One important criterion for identifying fragments from the same object is thread count (i.e. number of threads per centimeter) in the warp and weft directions. This is a tedious and time-consuming process. Computer science literature shows that current algorithms are not robust enough to solve the puzzle of archaeological textiles and proposes taking inspiration from the criteria that humans use [2-4]. To address this, we propose a framework for automatizing thread counting in textile images. We created a feature extractor, which captures thread count in vertical and horizontal directions. Thread count is usually measured by selecting several 1x1cm areas on the tapestries (we refer to this area as a patch), counting the threads and averaging the results. Archaeological textiles often have holes where threads are missing due to decomposition. The experts take this into account when they decide where to count. We modeled the thread count extraction as a pulse-counting process, inspired by how we intuitively count threads. For counting vertical threads, we trace the patch in the horizontal direction and count the thread by finding the number of occurrences of two consecutive vertical edges. Similarly for the horizontal threads we trace the patch in vertical directions. Our proposed thread flow begins with applying Otsu’s binary thresholding to the patch. Then we take all the pixel values for all columns in the same row to model the horizontal tracing of the patch. The pulse front is obtained by calculating the absolute approximate derivative of the trace. The number of pulses, which represent the number 𝑋(2: 𝑛) − 𝑋(1: 𝑛−1) of thread, is obtained by the number of non-zero elements of the absolute approximate derivative divided by two. This operation is repeated all the way from the top to bottom patch and the majority thread count is returned as the thread density of the patch. We compared our algorithm with the ground truth counted by experts. The preliminary results show that our method overestimates thread count. The final results will be presented at the conference. However, thread count features extracted with our method, provided promising results when used for clustering. Twelve out of 27 fragments clustered using thread count alone, were aligned with archaeologists’ hypotheses on which fragments belong together. The Oseberg Tapestry is a challenging case-study also because its thread systems consist of double threads, which introduces an additional complexity to the machine. The result for simpler scenarios will be also presented. Future work should explore more sophisticated methods for thresholding, such as Sobel to expose edges, and STRESS (Spatio-Temporal Retinex-inspired Envelope with Stochastic Sampling) enhancement preprocessing, to make them more separable.

• Havgar, Margrethe Kirby Hopstock (2021). Historiske kilder og kildebruk. [Internet]. Norsk digital læringsarena. Fulltekst i vitenarkiv Vis sammendrag

  En undervisningsfilm om ulike historiske kilder og arkeologi, og om hvilke spørsmål vi må stille oss når vi jobber med historiske kilder. Vi får bli med på Nasjonalbiblioteket og på den arkeologiske utgravningen av Gjellestadskipet.

• Rødsrud, Christian Løchsen; Havgar, Margrethe Kirby Hopstock & Klevan, Ole Andreas Laache (2020). Alltid viking. [Internet]. https://www.nrk.no/alltidviking/. Fulltekst i vitenarkiv Vis sammendrag

  Livestrøm, intervjuer og artikler fra en uke med utgravning av Gjellestadskipet i Halden, Viken.

Sjå alle arbeida i NVA