Abstract
Protecting and securing an information of digital media is very crucial due to illegal reproduction and modification of media has become an acute problem for copyright protection now a day. A Discrete Wavelet Transform (DWT) domain based robust watermarking scheme with online sequential extreme learning machine (OSELM) has been implemented on different images. The proposed scheme which combine DWT domain with OSELM and watermark is embedded as an ownership information. Experimental results demonstrate that the proposed watermarking scheme is imperceptible and robust against image processing and attacks such as blurring, cropping, noise addition, rotation, scaling, scaling-cropping, sharpening etc. Performance and efficacy of algorithm on watermarking scheme is determined and calibrated results are compared with other machine learning methods.
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Singh, R.P., Dabas, N., Chaudhary, V., Nagendra (2015). Online Sequential Extreme Learning Machine for Watermarking. In: Cao, J., Mao, K., Cambria, E., Man, Z., Toh, KA. (eds) Proceedings of ELM-2014 Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-14066-7_12
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DOI: https://doi.org/10.1007/978-3-319-14066-7_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14065-0
Online ISBN: 978-3-319-14066-7
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