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MSc projects on CV

Computer Vision Analysis of Heritage Engineering Drawings

Heritage engineering drawings stored in museums and archives contain valuable technical knowledge but are difficult to analyse and search due to noise, ageing, and limited metadata. This project aims to develop computer vision methods to analyse and extract information from historical mechanical drawings. The work may include preprocessing scanned images, detecting components, extracting annotations, and building visual indexing or retrieval tools. The outcomes will support digital preservation, archival search, and engineering heritage research. Example heritage datasets and collections can be accessed via the Museum of English Rural Life (MERL): https://merl.reading.ac.uk/collections/

360-degree imagery enables immersive capture of natural environments but poses challenges for automated ecological analysis due to distortion and wide field-of-view. This project will develop computer vision methods to analyse biodiversity elements visible within 360-degree images, focusing on visual cues that relate to high-biodiversity environments. This includes analysing visual spectrum properties (e.g., amount and distribution of green vegetation) as well as semantic elements (e.g., number of plants, trees, and habitat structures). The work will involve spherical image preprocessing, segmentation or detection modelling, and aggregation of ecological indicators. Example datasets are available via the Synthesis of Systematic Resources (SYN): https://syns.soton.ac.uk/