A contour-based approach to image compression

Paper


Scarmana, Gabriel. 2011. "A contour-based approach to image compression." 2011 International Conference on Digital Image Computing: Techniques and Application (DICTA 2011). Noosa, Australia 06 - 08 Dec 2011 Los Alamitos, CA. United States. https://doi.org/10.1109/DICTA.2011.38
Paper/Presentation Title

A contour-based approach to image compression

Presentation TypePaper
Authors
AuthorScarmana, Gabriel
Journal or Proceedings TitleProceedings of the 2011 International Conference on Digital Image Computing (DICTA 2011)
ERA Conference ID42717
Number of Pages5
Year2011
Place of PublicationLos Alamitos, CA. United States
ISBN9781457720062
Digital Object Identifier (DOI)https://doi.org/10.1109/DICTA.2011.38
Web Address (URL) of Paperhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6128680
Conference/Event2011 International Conference on Digital Image Computing: Techniques and Application (DICTA 2011)
Digital Image Computing Techniques and Applications
Event Details
Digital Image Computing Techniques and Applications
DICTA
Rank
B
B
B
Event Details
2011 International Conference on Digital Image Computing: Techniques and Application (DICTA 2011)
Parent
International Conference on Digital Image Computing: Techniques and Applications
Event Date
06 to end of 08 Dec 2011
Event Location
Noosa, Australia
Abstract

This paper presents an alternative spatial image compression method that can be directly applied to
compressing certain classes of grey-scale and/or colour (RGB, 24 bits) imagery of any size. The process involves the
vectorisation of digital images into contour maps with
subsequent converting of the contours to a pixel format.
Contours are often approximated by polygons (linear or
otherwise), and only the vertices of the polygons need to be
retained to recreate the original contour lines. The final
amount of storage depends crucially on the complexity of the
image and on the degree of approximation desired.
In this context, the compression process is based on filtering and eliminating those contours that may contain redundant information. Contours extracted from digital images may contain multiple redundant data (i.e. intersecting or nested contours), any of which might logically be used as a basis for discrimination and/or used in the reconstruction of an original captured image.
Depending on the applications, and the amount of contour lines employed in the reconstruction of an image, the process allows for various levels of image accuracy while preserving visual integrity and reducing compression artefacts.
The proposed method does not require special hardware and,
if combined with existing encoding schemes, can be efficiently used for image transmission purposes.

Keywordscontouring; image compression; image reconstruction; image processing; image editing
ANZSRC Field of Research 2020401304. Photogrammetry and remote sensing
490304. Optimisation
460306. Image processing
Public Notes

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Byline AffiliationsDepartment of Surveying and Land Information
Institution of OriginUniversity of Southern Queensland
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