SPATIAL NEIGHBORING HISTOGRAM FOR SHAPE-BASED IMAGE RETRIEVAL

Noramiza Hashim, Patrice Boursier, Hong Tat Ewe

Abstract

Man-made object recognition from ground level image requires a fast and efficient approach especially in a large image database. Our work focuses on recognizing buildings based on a shape-based histogram descriptor. A 2-dimensional histogram is generated from gradient direction information of edge pixels and local spatial analysis of its neighbors. The edge direction histogram is a global representation of edge pixels. The neighborhood structure is coded in a 4-bit binary representation which offers a simple and efficient way to incorporate local spatial data into the histogram. We find that the proposed spatial neighboring histogram increases the retrieval precision by approximately 10% compared to other shape-based histogram methods.

References

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Paper Citation


in Harvard Style

Hashim N., Boursier P. and Tat Ewe H. (2008). SPATIAL NEIGHBORING HISTOGRAM FOR SHAPE-BASED IMAGE RETRIEVAL . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 256-259. DOI: 10.5220/0001075302560259


in Bibtex Style

@conference{visapp08,
author={Noramiza Hashim and Patrice Boursier and Hong Tat Ewe},
title={SPATIAL NEIGHBORING HISTOGRAM FOR SHAPE-BASED IMAGE RETRIEVAL},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={256-259},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001075302560259},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - SPATIAL NEIGHBORING HISTOGRAM FOR SHAPE-BASED IMAGE RETRIEVAL
SN - 978-989-8111-21-0
AU - Hashim N.
AU - Boursier P.
AU - Tat Ewe H.
PY - 2008
SP - 256
EP - 259
DO - 10.5220/0001075302560259