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Picture Search

See the Advanced Options panel for more detail than ever before. Example queries:


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See how imense® Web 3.0 Search can work for you

Web 3.0 - Search inside the image

Can your users find the image they need? Maybe they want a couple facing right, with copy space in the top? Or a close-up of two children with ginger hair and copy space? Finding specific images can sometimes be hard with traditional text-based search. Now with the imense® Web 3.0 product your users can unearth relevant images even if they don’t have the correct keywords. Our unique platform combines content-based image recognition with traditional metadata, allowing your users to search inside the image — and providing more relevant images than your competitors.

Here’s how

Web 3.0 diagram

Step 1

Image features are extracted in the classification process

Step 2

Features are stored in our visual index, along with metadata.

Step 3

Users query our visual index and your metadata via text to unearth relevant images.


  • Semantic search – allows users to pose queries traditional systems can’t understand such as “Beach without people”
  • Statistical Ranking – the system understands how relevant a concept is to an image. Results are ordered based on this.
  • Spatial Search – allows users to pose queries with spatial relevance such as “on the left”, “on the right”, “above” or “below”.

Web 3.0 image search allows users to search image collections easier than ever before, taking them to the right image faster than ever before. This revolutionary approach allows image agencies and search engines to retain existing and attract new users.


Images are processed through a classification system using content based image retrieval techniques developed by our founders Dr Christopher Town and Dr David Sinclair. The system uses the ontology based visual information processing technique pioneered by them in 2004. Once images have been processed, visual features are stored within a visual ontology. Using our unique semantic image query language, users can type keywords or simple natural language terms which are then processed by the system, which in turn queries the visual ontology for the most statistically relevant results.


Image agencies; Publishing Groups; Digital Asset Management Providers;Search engines; Photosharing and Social Networking sites can all use Web 3.0 image search, in order to dramatically improve the accuracy and depth of search to attract new users.