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Authors: Salih Arda Boluk and M. Fatih Demirci

Affiliation: TOBB University of Economics and Technology, Turkey

Keyword(s): Shape Retrieval, Shape Matching, Medial Axis Graph, Earth Mover’s Distance.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Shape Representation and Matching

Abstract: In recent decades, the need for efficient and effective image search from large databases has increased. In this paper, we present a novel shape matching framework based on structures that are likely to exist in similar shapes. After representing shapes as medial axis graphs, where vertices show skeletons and edges connect nearby skeletons, we determine the branches connecting or representing shape’s different parts. Using the shortest path distance from each vertex (skeleton) to each of the branches, we effectively retrieve similar shapes to the given query through a transportation-based distance function. A set of shape retrieval experiments including the comparison with two previous approaches demonstrate the proposed algorithm’s effectiveness and perturbation experiments present its robustness.

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Paper citation in several formats:
Boluk, S. and Demirci, M. (2015). Shape Classification based on Skeleton-branch Distances. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 353-359. DOI: 10.5220/0005300503530359

@conference{visapp15,
author={Salih Arda Boluk. and M. Fatih Demirci.},
title={Shape Classification based on Skeleton-branch Distances},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={353-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005300503530359},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Shape Classification based on Skeleton-branch Distances
SN - 978-989-758-090-1
IS - 2184-4321
AU - Boluk, S.
AU - Demirci, M.
PY - 2015
SP - 353
EP - 359
DO - 10.5220/0005300503530359
PB - SciTePress