Abstract
Rock art is an archaeological term for human-made markings on stone, including carved markings, known as petroglyphs, and painted markings, known as pictographs. It is believed that there are millions of petroglyphs in North America alone, and the study of this valued cultural resource has implications even beyond anthropology and history. Surprisingly, although image processing, information retrieval and data mining have had a large impact on many human endeavors, they have had essentially zero impact on the study of rock art. In this work we identify the reasons for this, and introduce a novel distance measure and algorithms which allow efficient and effective data mining of large collections of rock art.
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Acknowledgements
This work was funded by NSF 0803410 and NSF 0808770. Field work for this project was funded by a National Geographic Society/Waitt Grant. We would like to thank the many donors of datasets, particularly Dr. Robert Mark and Evelyn Billo of www.rupestrian.com, Taryn T. Rampley of UCR and the Document Analysis Group of the Computer Vision Center in Universitat Autònoma de Barcelona.
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Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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Zhu, Q., Wang, X., Keogh, E. et al. An efficient and effective similarity measure to enable data mining of petroglyphs. Data Min Knowl Disc 23, 91–127 (2011). https://doi.org/10.1007/s10618-010-0200-z
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DOI: https://doi.org/10.1007/s10618-010-0200-z