Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering

A Comparative Study of Local Image Feature Description

Authors
Lifen Zhou, Yanlin Tao
Corresponding Author
Lifen Zhou
Available Online July 2016.
DOI
10.2991/icsnce-16.2016.66How to use a DOI?
Keywords
Local feature; Feature detection; Feature description; SIFT
Abstract

In view of the local image feature description algorithm of recent year, we compare them with SIFT, which is a classic algorithm. We found the gap of every kind of description algorithm with some image transformations, and this can be a reference when feature description algorithm used in some application of computer vision. Our results show that MROGH and MRRID has the best performance, and then is LIOP, DAISY and HRI-CSLTP are better than SIFT in some image transformation.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
Series
Advances in Engineering Research
Publication Date
July 2016
ISBN
10.2991/icsnce-16.2016.66
ISSN
2352-5401
DOI
10.2991/icsnce-16.2016.66How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lifen Zhou
AU  - Yanlin Tao
PY  - 2016/07
DA  - 2016/07
TI  - A Comparative Study of Local Image Feature Description
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 337
EP  - 343
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.66
DO  - 10.2991/icsnce-16.2016.66
ID  - Zhou2016/07
ER  -