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Optimization of use-wear detection and characterization on stone tool surfaces.

ABSTRACT: Debates and doubt around the interpretation of use-wear on stone tools called for the development of quantitative analysis of surfaces to complement the qualitative description of traces. Recently, a growing number of studies showed that prehistoric activities can be discriminated thanks to quantitative characterization of stone tools surface alteration due to use. However, stone tool surfaces are microscopically very heterogeneous and the calculated parameters may highly vary depending on the areas selected for measurement. Indeed, it may be impacted by the effects from the raw material topography and not from the altered zones only, if non-altered part of the surface is included in the measurement. We propose here to discuss this issue and present a workflow involving the use of masks to separate worn and unworn parts of the surface. Our results show that this step of extraction, together with suitable filtering, could have a high impact on the optimization of the detection and thus characterization of use traces. This represents the basis for future automatic routines allowing the detection, extraction and characterization of wear on stone tools.

SUBMITTER: Antony B

PROVIDER: S-EPMC8683413 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The identification of the use of stone tools through use-wear analysis was one the major methodological advances in Prehistoric Archaeology during the second half of the 20th century. Studies of use-wear analysis have decisively contributed to a better understanding of the cognitive capacities and the socio-economic organization of Prehistoric societies. Among use-wear traces, microwear polish is the most relevant evidence, as it allows the identification of the worked materials (i.e. wood, antler, hide, bone, stone…). This identification is currently carried out through the qualitative and visual comparison of experimental and archaeological tools. During the last decade, confocal microscopy is allowing the quantitative identification of the worked material through the texture analysis of microwear polish. Previous tests have accounted for the variability of use-wear traces as caused by different types of worked material. However, how the intensity of use, which is widely recognized as an important factor conditioning microwear polish characteristics, affects our capacity to identify the worked materials is poorly understood. This research addresses the dynamic nature of microwear polish through confocal microscopy and texture analysis. This research shows that use-wear polishing is a dynamic process and surface texture evolves continuously during the working time. The evolution fits a logarithmic function, so most texture modification takes place during the first phases of work. The way in which polish texture evolves through time differs from one contact material to the other. We demonstrate that, despite the dynamic nature of use-wear polish, different worked materials can be discriminated. However, some overlapping between used and unused surfaces and between worked materials occurs in the first stages of use. Moreover, polishes of similar characteristics (i.e. bone and antler) can show similar texture at advanced stages of use. These problems in identification can be in good measure overcome by creating dynamic models of polish texture in which not only the worked material but also the time of use is considered.

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Optimization of use-wear detection and characterization on stone tool surfaces.

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