Visual Analysis & Collection Research
Image analysis
Image analysis makes visual collection material more accessible, more richly described and easier to search. By automatically analysing images for content, characteristics and patterns, an additional layer of insight emerges to support research, access and public use.
In museums, archives and heritage organisations, images play a central role. Yet images are not always easy to describe fully. Photographs, scans, artworks, object registrations and other visual material often contain more information than existing metadata captures. With image analysis, you add a new layer of enrichment to your collection. AI helps recognise visual characteristics, objects, scenes, patterns and other content elements in image material.
More insight into visual material
Image analysis helps examine images and other visual collection material systematically. By automatically identifying characteristics and content elements, it provides more control over what is visible in images.
Support for description and metadata
Many visual collections are only partly described. Image analysis can help enrich metadata by recognising objects, themes, visual characteristics or recurring elements.
Making relationships and patterns visible
Analysing images at scale can reveal similarities and recurring patterns, such as motifs, object types, compositions or visual styles.
Better accessibility of image collections
When images are described more richly and consistently, they become easier to search and access for research, education, curation and public-facing applications.
Valuable for large and diverse collections
In large or heterogeneous image collections, it is often difficult to gain an overview quickly. Image analysis helps explore large volumes of visual material more efficiently.
Technology supporting expertise
AI supports the signalling and structuring of visual information, while substantive assessment and interpretation remain with the people who know the collection.
What it delivers
Richer description of image material
Add visual characteristics, objects and content signals to existing metadata.
Faster insight into large collections
Analyse large volumes of image material more efficiently and gain overview faster.
New research access points
Discover patterns, similarities and relationships that would otherwise remain less visible.
Better findability and accessibility
Make image collections more useful for research, education and public access.
Human in the loop
In heritage and collection management, care is essential. We therefore work according to the principle of human in the loop: AI makes suggestions, while people assess relevance, quality and context.