Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497536
Title: Area-based vectorisation of colour cartoon images
Author: Gardiner, Michael John
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2006
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Abstract:
Cartoon images are often stored as pixel-based, raster data. This format is not the most appropriate for representing cartoon images that are initially drawn as geometric areas of colour. Raster images cannot be scaled without creating pixelisation artefacts and modification of such images must be performed pixel by pixel. A vector-based representation is a more suitable format for storing cartoon images. This thesis investigates a novel process for converting colour raster images into colour vector images. The process has been refined to facilitate the conversion of colour cartoon images, natively stored as raster data, into a scalable vector representation consisting of areas of uniform colours. The process is composed of a number of stages which are reviewed in some detail. These include; colour quantisation, colour decomposition, shape outlining, path tracing, path simplification, rendering and storage. An investigation into the use of colours in different types of images has been performed and used to improve the colour quantisation stage of the process which was noted to be problematic. Using the enhanced colour quantisation scheme together with additional novel optimisations an efficient colour area-based vectorisation system has been produced. The system has been extended to process multiple sequential images to support efficient conversion of cartoon video sequences into scalable vector animation. The developed colour area-based vectorisation system has been applied to a database of raster cartoon images. The generated vector representation is shown to offer a number of benefits including reduced storage requirements, the ability to render at higher resolutions without creating pixelation artefacts and simplified image manipulation for future modifications.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.497536  DOI: Not available
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