Objective Quality Metrics in Correlation with Subjective Quality Metrics for Steganography

Wazirali, R; Slehat, S; Chaczko, Z; Borowik, G; Carrión, L

Objective Quality Metrics in Correlation with Subjective Quality Metrics for Steganography

Wazirali, R Slehat, S Chaczko, Z

Borowik, G Carrión, L

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2015 Asia-Pacific Conference on Computer-Aided System Engineering, APCASE 2015, 2015, pp. 238 - 245
Issue Date:: 2015-10-01

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Field	Value	Language
dc.contributor.author	Wazirali, R	en_US
dc.contributor.author	Slehat, S	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Borowik, G	en_US
dc.contributor.author	Carrión, L	en_US
dc.date.available	2015-06-01	en_US
dc.date.issued	2015-10-01	en_US
dc.identifier.citation	Proceedings - 2015 Asia-Pacific Conference on Computer-Aided System Engineering, APCASE 2015, 2015, pp. 238 - 245	en_US
dc.identifier.isbn	9781479975884	en_US
dc.identifier.uri	http://hdl.handle.net/10453/37167
dc.description.abstract	© 2015 IEEE. The main goal of hiding data is to conceal the very existence of the hidden information, therefore there is a significant demand for steganographic approaches that can ensure imperceptibility of such infromation. However, there is a limited corresponding evaluation parameters available. Most of the studies use the Peak Signal to Noise Ratio (PSNR) as a metric for imperceptibility evaluation, although it could provide less accurate results than the Human Visual System (HVS) evaluation. This paper provides a review of the existent evaluation metrics that are used to assess the quality of steganography. The examination of the correlation between the existing objective and subjective metrics is also conducted. Pixel differences metrics have a poor correlation with the subjective metrics, hence the HSV based metrics have better correlation than pixel metrics.	en_US
dc.relation.ispartof	Proceedings - 2015 Asia-Pacific Conference on Computer-Aided System Engineering, APCASE 2015	en_US
dc.relation.isbasedon	10.1109/APCASE.2015.49	en_US
dc.title	Objective Quality Metrics in Correlation with Subjective Quality Metrics for Steganography	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)/Connected Intelligence Centre
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. The main goal of hiding data is to conceal the very existence of the hidden information, therefore there is a significant demand for steganographic approaches that can ensure imperceptibility of such infromation. However, there is a limited corresponding evaluation parameters available. Most of the studies use the Peak Signal to Noise Ratio (PSNR) as a metric for imperceptibility evaluation, although it could provide less accurate results than the Human Visual System (HVS) evaluation. This paper provides a review of the existent evaluation metrics that are used to assess the quality of steganography. The examination of the correlation between the existing objective and subjective metrics is also conducted. Pixel differences metrics have a poor correlation with the subjective metrics, hence the HSV based metrics have better correlation than pixel metrics.

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http://hdl.handle.net/10453/37167