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Dense-Field Skeleton-Based Image Representations

Meiburg, Y. (2011) Dense-Field Skeleton-Based Image Representations. Master's Thesis / Essay, Computing Science.

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Skeletons are good 2D or 3D shape descriptors. However, so far they have only been used to encode simple, compact, closed boundaries such as isolines or isosurfaces. In this thesis we study an extension of classical 2D multiscale skeletons to a new notion: dense field skeletons. Dense skeletons will be used to encode an entire 2D field, such as a monochrome image, into a scale-space of skeletons. By this method, operations such as image compression, progressive image encoding and/or transmission will be approached using the robust, well-proven, descriptive powers of skeleton features. Efficient storage is achieved by skeleton simplification and a state history based neighbour-coding scheme to encode skeleton-trees. The result is then further compressed using the Lempel-Ziv-Markov Chain Algorithm (LZMA). Reconstruction is done by inflating skeletons per layer, and smoothly interpolating the edges to reduce sharp transitions on high compression.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Computing Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:46
Last Modified: 15 Feb 2018 07:46

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