Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/18524
Title: Weighting optimization with neural network for photo-response-non-uniformity-based source camera identification
Authors: Shi, C
Law, NF 
Leung, HF 
Siu, WC 
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014, 2014, 7041642 How to cite?
Abstract: Identifying the source camera of images is becoming increasingly important nowadays. A popular approach is to use a type of pattern noise called photo-response non-uniformity (PRNU). Despite that, the PRNU-based approach is sensitive towards scene content and image intensity. The identification is poor in areas having low or saturated intensity, or in areas with complicated texture. To solve the scene content problem, a weighting scheme that considers the reliability of image regions has been proposed in this paper. The proposed method uses an artificial neural network to determine the optimal weighting of each sub-block in images. Then the weightings are used to help determine the reliability of that region in identifying the source camera. The proposed method is tested against several state-of-art methods. The experiments show an encouraging result in terms of the ROC curve.
Description: 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014, 9-12 December 2014
URI: http://hdl.handle.net/10397/18524
ISBN: 9.79E+12
DOI: 10.1109/APSIPA.2014.7041642
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

1
Last Week
0
Last month
0
Citations as of Aug 18, 2017

Page view(s)

39
Last Week
1
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.