Exploring the effectiveness of similarity-based visualisations for colour-based image retrieval

  • William Plant

    Student thesis: Doctoral ThesisDoctor of Philosophy


    In April 2009, Google Images added a filter for narrowing search results by colour. Several other
    systems for searching image databases by colour were also released around this time. These colour-based image retrieval systems enable users to search image databases either by selecting colours from a graphical palette (i.e., query-by-colour), by drawing a representation of the colour layout sought (i.e., query-by-sketch), or both. It was comments left by readers of online articles describing these
    colour-based image retrieval systems that provided us with the inspiration for this research. We were surprised to learn that the underlying query-based technology used in colour-based image retrieval systems today remains remarkably similar to that of systems developed nearly two decades ago. Discovering this ageing retrieval approach, as well as uncovering a large user demographic requiring image search by colour, made us eager to research more effective approaches for colour-based
    image retrieval. In this thesis, we detail two user studies designed to compare the effectiveness of
    systems adopting similarity-based visualisations, query-based approaches, or a combination of both, for colour-based image retrieval. In contrast to query-based approaches, similarity-based visualisations
    display and arrange database images so that images with similar content are located closer
    together on screen than images with dissimilar content. This removes the need for queries, as users can instead visually explore the database using interactive navigation tools to retrieve images from the database. As we found existing evaluation approaches to be unreliable, we describe how we
    assessed and compared systems adopting similarity-based visualisations, query-based approaches, or both, meaningfully and systematically using our Mosaic Test - a user-based evaluation approach in which evaluation study participants complete an image mosaic of a predetermined target image using the colour-based image retrieval system under evaluation.
    Date of Award2013
    Original languageEnglish
    SupervisorIan T. Nabney (Supervisor) & Joanna M Lumsden (Supervisor)


    • image databases
    • image retrieval
    • colour
    • visualisation
    • evaluation

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