Paper Info
Title
A Multimedia Watermarking Technique Based On Svms
Abstract
In this paper we present an improved support vector machines (SVMs) watermarking system for still images and video sequences. By a thorough study on feature selection for training SVM, the proposed system shows significant improvements on computation efficiency and robustness to various attacks. The improved algorithm is extended to be a scene-based video watermarking technique. In a given scene, the algorithm uses the first h' frames to train an embedding SVM, and uses the trained SVM to watermark the rest of the frames. In the extracting phrase, the detector uses only the center h frames of the first h' frames to train an extracting SVM. The final extracted watermark in a given scene is the average of watermarks extracted from the remaining frames. Watermarks are embedded in l longest scenes of a video such that it is computationally efficient and capable to resist possible frames swapping/deleting/duplicating attacks. Two collusion attacks, namely temporal frame averaging and watermark estimation remodulation, on video watermarking are discussed and examined. The proposed video watermarking algorithm is shown to be robust to compression and collusion attacks, and it is novel and practical for SVM-applications.
Year
DOI
Venue
2008
10.1142/S0218001408006934
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Digital watermarking, Support Vector Machines (SVMs), Tolerable Position Map (TPM), video watermarking, collusion attacks, Temporal Frame Averaging (TFA), Watermark Estimation Remodulation (WER)
Digital watermarking,Feature selection,Computer science,Support vector machine,Speech recognition,Artificial intelligence,Machine learning,Support vector machines svms
Journal
Volume
Issue
ISSN
22
8
0218-0014
Citations 
PageRank 
References 
2
0.38
8
Authors
3
Name
Order
Citations
PageRank
Chia-Jen Wang1173.25
Shwu-huey Yen2429.07
Patrick S. Wang351.80