The nature of statistical learning theory
The nature of statistical learning theory
Digital watermarking
The first 50 years of electronic watermarking
EURASIP Journal on Applied Signal Processing - Emerging applications of multimedia data hiding
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
An Audio Watermarking Technique That Is Robust Against Random Cropping
Computer Music Journal
Machine learning based adaptive watermark decoding in view of anticipated attack
Pattern Recognition
Kernelized fuzzy attribute C-means clustering algorithm
Fuzzy Sets and Systems
An integrated on-line audio watermark decoding scheme for broadcast monitoring
Multimedia Tools and Applications
DWT-Based Audio Watermarking Using Support Vector Regression and Subsampling
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Fidelity-guaranteed robustness enhancement of blind-detection watermarking schemes
Information Sciences: an International Journal
A new approach for optimization in image watermarking by using genetic algorithms
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
In this paper, we propose an adaptive audio watermarking scheme based on kernel fuzzy c-means (KFCM) clustering algorithm, which possesses robust ability against common signal processing and desynchronization attacks. The original audio signal is partitioned into audio frames and then each audio frame is further divided as two sub-frames. In order to resist desynchronization attacks, we embed a synchronization code into first sub-frame of each audio frame by using a mean quantization technique in temporal domain. Moreover, watermark signal is hid into DWT coefficients of second sub-frame of each audio frame by using an energy quantization technique. A local audio feature data set extracted from all audio frames is used to train a KFCM. The well-trained KFCM is used to adaptively control quantization steps in above two quantization techniques. The experimental results show the proposed scheme is robust to common signal processing (such as MP3 lossy compression, noise addition, filtering, re-sampling, re-quantizing) and desynchronization attacks (random cropping, pitch shifting, amplitude variation, time-scale modification, jittering).