NDLI: Support Vector Machine and hyperplanes in digital watermark detection

Content Provider	IEEE Xplore Digital Library
Author	Then, H.H.P.
Copyright Year	2007
Description	Author affiliation: Swinburne Univ. of Technol., Kuching (Then, H.H.P.)
Abstract	Correlation detector (CD) has been widely used to determine whether a legitimate watermark exists in a suspected watermarked object. The watermarked and unwatermarked images are perceived as positive and negative class respectively. Hence, support vector machine (SVM) is used as the classifier of water-marked and unwatermarked digital image due to its ability of separating both linearly and non-linearly separable data. Hyperplanes of various detectors are briefly elaborated to show how SVM's hyperplane is suitable for Stirmark attacked watermarked image. Cox's spread spectrum watermarking scheme is used to embed the watermark into digital images. Then, SVM is trained with both the watermarked and unwatermarked images. Receiver operating characteristics graphs are plotted to assess the false positive and false negative probability of both the CD and SVM classifier. Both watermarked and unwatermarked images are later attacked under Stirmark, and then tested on the CD and SVM classifier. The preprocessing and optimal parameters setting enable the trained SVM to achieve substantially better results than those resulting from the CD.
Starting Page	1
Ending Page	4
File Size	418696
Page Count	4
File Format	PDF
ISBN	9781424412716
DOI	10.1109/TENCON.2007.4429122
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-30
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Watermarking Support vector machine classification Detectors Payloads Neural networks Digital images Robustness Spread spectrum communication Multi-layer neural network
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Digital Audio Watermarking Algorithm based on Neural Networks

Support vector machine models for freeway incident detection

Optimum Detection for Spread-Spectrum Watermarking that Employs Self-masking

Binary Classification Using Linear SVM Pyramidal Tree

Estimation of multi-pattern-to-single-pattern functions by combining feedforward neural networks and support vector machines

Neural network ensemble and support vector machine classifiers for the analysis of remotely sensed data: a comparison

Maximizing margins of multilayer neural networks

A pattern classification method based on GA and SVM

SVM multi-classifier and Web document classification

Support Vector Machine and hyperplanes in digital watermark detection

Similar Documents

Digital Audio Watermarking Algorithm based on Neural Networks

Support vector machine models for freeway incident detection

Optimum Detection for Spread-Spectrum Watermarking that Employs Self-masking

Binary Classification Using Linear SVM Pyramidal Tree

Estimation of multi-pattern-to-single-pattern functions by combining feedforward neural networks and support vector machines

Neural network ensemble and support vector machine classifiers for the analysis of remotely sensed data: a comparison

Maximizing margins of multilayer neural networks

A pattern classification method based on GA and SVM

SVM multi-classifier and Web document classification

Support Vector Machine and hyperplanes in digital watermark detection