Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29447
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dc.contributor.authorLeung, Kam Shek Simon-
dc.date.accessioned2019-05-08T14:30:55Z-
dc.date.available2019-05-08T14:30:55Z-
dc.date.issued1991-
dc.identifier.urihttp://hdl.handle.net/1893/29447-
dc.description.abstractThis thesis describes an image segmentation technique based on watersheds, a clustering technique which does not use spatial information, but relies on multispectral images. These are captured using a monochrome camera and narrow-band filters; we call this color segmentation, although it does not use color in a physiological sense. A major part of the work is testing the method developed using different color images. Starting with a general discussion of image processing, the different techniques used in image segmentation are reviewed, and the application of mathematical morphology to image processing is discussed. The use of watersheds as a clustering technique in two- dimensional color space is discussed, and system performance illustrated. The method can be improved for industrial applications by using normalized color to eliminate the problem of shadows. These methods are extended to segment the image into regions recursively. Different types of color images including both man made color images, and natural color images have been used to illustrate performance. There is a brief discussion and a simple illustration showing how segmentation can be used in image compression, and of the application of pyramidal data structures in clustering for coarse segmentation. The thesis concludes with an investigation of the methods which can be used to improve these segmentation results. This includes edge extraction, texture extraction, and recursive merging.en_GB
dc.language.isoenen_GB
dc.publisherUniversity of Stirlingen_GB
dc.subject.lcshImage analysisen_GB
dc.subject.lcshImage processingen_GB
dc.subject.lcshImage segmentation.en_GB
dc.subject.lcshColoren_GB
dc.titleImage processing by region extraction using a clustering approach based on coloren_GB
dc.typeThesis or Dissertationen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnameDoctor of Philosophyen_GB
Appears in Collections:eTheses from Faculty of Natural Sciences legacy departments

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