2025/11/27 by Juan Francisco Palomeque‐González, Palomeque-Gonzalez, Juan
Computer Science · Earth and Planetary Sciences · Social Sciences · #Archaeology and ancient environmental studies #Computer Vision and Pattern Recognition (cs.CV) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Pleistocene-Era Hominins and Archaeology
paper · pdf · doi:10.48550/arxiv.2512.11817
openalex publication_date 2025/11/27 · openalex created_date 2025/12/17 · openalex updated_date 2026/07/28
This technical note presents a reproducible workflow for converting a legacy archaeological image collection into a structured and segmentation ready dataset. The case study focuses on the Lower Palaeolithic hand axe and biface collection curated by the Archaeology Data Service (ADS), a dataset that provides thousands of standardised photographs but no mechanism for bulk download or automated processing. To address this, two open source tools were developed: a web scraping script that retrieves all record pages, extracts associated metadata, and downloads the available images while respecting ADS Terms of Use and ethical scraping guidelines; and an image processing pipeline that renames files using UUIDs, generates binary masks and bounding boxes through classical computer vision, and stores all derived information in a COCO compatible Json file enriched with archaeological metadata. The original images are not redistributed, and only derived products such as masks, outlines, and annotations are shared. Together, these components provide a lightweight and reusable approach for transforming web based archaeological image collections into machine learning friendly formats, facilitating downstream analysis and contributing to more reproducible research practices in digital archaeology.