Proceedings of the 2012 National Conference on Information Technology and Computer Science

Study on feature extraction method of Han Dynasty stone carving images

Authors
Juan Wang, Man Tang
Corresponding Author
Juan Wang
Available Online November 2012.
DOI
https://doi.org/10.2991/citcs.2012.215How to use a DOI?
Keywords
Han Dynasty stone carving images; feature extraction; image retrieval; multi-feature fusion
Abstract
Han Dynasty stone carving is Chinese nation's outstanding cultural heritage, how to protect and promote it is an historical responsibility. In recent years, there has been a lot of research on the Han Dynasty stone carving, and has achieved certain results. But the digital research on it is still very rare. This is mainly because the own characteristics of Han Dynasty stone carving images make feature extraction become difficult. Feature extraction is the key point of Han Dynasty stone carving's digital research, which directly affects the accuracy of image retrieval and the efficiency of image matching algorithm. This paper based on the analysis of the characteristics of Han Dynasty stone carving images and the existing image feature extraction methods, puts forward a scheme for feature extraction of Han Dynasty stone carving images which adopts multi- feature fusion.
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Proceedings
2012 National Conference on Information Technology and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
November 2012
ISBN
978-94-91216-39-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/citcs.2012.215How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Juan Wang
AU  - Man Tang
PY  - 2012/11
DA  - 2012/11
TI  - Study on feature extraction method of Han Dynasty stone carving images
BT  - 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 846
EP  - 849
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.215
DO  - https://doi.org/10.2991/citcs.2012.215
ID  - Wang2012/11
ER  -