Abstract
Copyright protection for multimedia data owners is of crucial importance as the duplication of multimedia data has become easily with the advent of Internet and digital multimedia technology. Current digital watermarking techniques for preserving the product ownership are rule-based and not directly deal with the data synchronization, therefore their decoding performance reduces significantly when the watermarked data is transmitted through a real communication channel. This paper proposes a pattern recognition framework to build a new blind watermark scheme for electroencephalography (EEG) data. Embedding a watermark is based on modifying mean modulation relationship of approximation coefficient in wavelet domain. Retrieving this watermark is done effectively using Support vector data description (SVDD) models trained with the correlation between modified frequency coefficients and the watermark sequence in wavelet domain. Experimental results show that the proposed scheme provides good imperceptibility and more robust against various signal processing techniques and common attacks such as random cropping, noise addition, low-pass filtering, and resampling.
Original language | English |
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Title of host publication | 2016 23rd International Conference on Pattern Recognition, ICPR 2016 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 955-960 |
Number of pages | 6 |
ISBN (Electronic) | 9781509048472 |
ISBN (Print) | 9781509048489 |
DOIs | |
Publication status | Published - 4 Dec 2016 |
Event | 23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico Duration: 4 Dec 2016 → 8 Dec 2016 |
Conference
Conference | 23rd International Conference on Pattern Recognition, ICPR 2016 |
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Country | Mexico |
City | Cancun |
Period | 4/12/16 → 8/12/16 |