IEICE TRANSACTIONS on Information
Intelligent Extraction of a Digital Watermark from a Distorted Image
Summary :
We present a novel approach to developing Machine Learning (ML) based decoding models for extracting a watermark in the presence of attacks. Statistical characterization of the components of various frequency bands is exploited to allow blind extraction of the watermark. Experimental results show that the proposed ML based decoding scheme can adapt to suit the watermark application by learning the alterations in the feature space incurred by the attack employed.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.7 pp.2072-2075
- Publication Date
- 2008/07/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.7.2072
- Type of Manuscript
- LETTER
- Category
- Application Information Security
Authors
Keyword
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Asifullah KHAN, Syed Fahad TAHIR, Tae-Sun CHOI, "Intelligent Extraction of a Digital Watermark from a Distorted Image" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 7, pp. 2072-2075, July 2008, doi: 10.1093/ietisy/e91-d.7.2072.
Abstract: We present a novel approach to developing Machine Learning (ML) based decoding models for extracting a watermark in the presence of attacks. Statistical characterization of the components of various frequency bands is exploited to allow blind extraction of the watermark. Experimental results show that the proposed ML based decoding scheme can adapt to suit the watermark application by learning the alterations in the feature space incurred by the attack employed.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.7.2072/_p
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@ARTICLE{e91-d_7_2072,
author={Asifullah KHAN, Syed Fahad TAHIR, Tae-Sun CHOI, },
journal={IEICE TRANSACTIONS on Information},
title={Intelligent Extraction of a Digital Watermark from a Distorted Image},
year={2008},
volume={E91-D},
number={7},
pages={2072-2075},
abstract={We present a novel approach to developing Machine Learning (ML) based decoding models for extracting a watermark in the presence of attacks. Statistical characterization of the components of various frequency bands is exploited to allow blind extraction of the watermark. Experimental results show that the proposed ML based decoding scheme can adapt to suit the watermark application by learning the alterations in the feature space incurred by the attack employed.},
keywords={},
doi={10.1093/ietisy/e91-d.7.2072},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Intelligent Extraction of a Digital Watermark from a Distorted Image
T2 - IEICE TRANSACTIONS on Information
SP - 2072
EP - 2075
AU - Asifullah KHAN
AU - Syed Fahad TAHIR
AU - Tae-Sun CHOI
PY - 2008
DO - 10.1093/ietisy/e91-d.7.2072
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2008
AB - We present a novel approach to developing Machine Learning (ML) based decoding models for extracting a watermark in the presence of attacks. Statistical characterization of the components of various frequency bands is exploited to allow blind extraction of the watermark. Experimental results show that the proposed ML based decoding scheme can adapt to suit the watermark application by learning the alterations in the feature space incurred by the attack employed.
ER -
English
