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Authors: Matthew van der Zwan 1 ; Yuri Meiburg 1 and Alexandru Telea 2

Affiliations: 1 University of Groningen, Netherlands ; 2 University of Groningen and University of Medicine and Pharmacy Carol Davila, Netherlands

Keyword(s): Medial Axes, Image Segmentation, Shape Analysis.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping ; Shape Representation and Matching ; Visual Attention and Image Saliency

Abstract: We present dense medial descriptors, a new technique which generalizes the well-known medial axes to encode and manipulate whole 2D grayvalue images, rather than binary shapes. To compute our descriptors, we first reduce an image to a set of threshold-sets in luminance space. Next, we compute a simplified representation of each threshold-set using a noise-resistant medial axis transform. Finally, we use these medial axis transforms to perform a range of operations on the input image, from perfect reconstruction to segmentation, simplification, and artistic effects. Our pipeline can robustly handle any 2D grayscale image, is easy to use, and allows an efficient CPU or GPU-based implementation. We demonstrate our dense medial descriptors with several image-processing applications.

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Paper citation in several formats:
Zwan, M.; Meiburg, Y. and Telea, A. (2013). A Dense Medial Descriptor for Image Analysis. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP; ISBN 978-989-8565-47-1; ISSN 2184-4321, SciTePress, pages 285-293. DOI: 10.5220/0004279202850293

@conference{visapp13,
author={Matthew van der Zwan. and Yuri Meiburg. and Alexandru Telea.},
title={A Dense Medial Descriptor for Image Analysis},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP},
year={2013},
pages={285-293},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004279202850293},
isbn={978-989-8565-47-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP
TI - A Dense Medial Descriptor for Image Analysis
SN - 978-989-8565-47-1
IS - 2184-4321
AU - Zwan, M.
AU - Meiburg, Y.
AU - Telea, A.
PY - 2013
SP - 285
EP - 293
DO - 10.5220/0004279202850293
PB - SciTePress