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Cortina 2005

Hol, M. and Kalsbeek F.E. (2005) Cortina 2005. Master's Thesis / Essay, Computing Science.

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Searching for images in a large scale database with nothing but keywords might not be optimal. Images are better described by their visual content rather than by keywords. Currently, the majority of the existing content based image retrieval systems rely on small, sometimes artificial, image databases. We propose a large scale content based image retrieval system with an initial keyword based image search. The visual information is extracted from images based on three features: shape, color and texture. To cope with the scalability, several measures have been taken like clustering and the use of categories. The result is a scalable system that works well for images which are distinct in one or more of the three features. For more complex images, future work should involve image segmentation

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Computing Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:30
Last Modified: 15 Feb 2018 07:30

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