Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10362555 | Signal Processing: Image Communication | 2014 | 11 Pages |
Abstract
Chain codes are the most size-efficient representations of rasterised binary shapes and contours. This paper considers a new lossless chain code compression method based on move-to-front transform and an adaptive run-length encoding. The former reduces the information entropy of the chain code, whilst the latter compresses the entropy-reduced chain code by coding the repetitions of chain code symbols and their combinations using a variable-length model. In comparison to other state-of-the-art compression methods, the entropy-reduction is highly efficient, and the newly proposed method yields, on average, better compression.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Borut Žalik, Niko LukaÄ,