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Dabas, Neelam
- A Novel Blind Digital Watermarking Based on SVD and Extreme Learning Machine
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Authors
Affiliations
1 Computer Science Department, University of Delhi, Delhi, IN
2 Computer Science Department, DDUC, University of Delhi, Delhi, IN
3 Computer Science Department, BNC, University of Delhi, Delhi, IN
1 Computer Science Department, University of Delhi, Delhi, IN
2 Computer Science Department, DDUC, University of Delhi, Delhi, IN
3 Computer Science Department, BNC, University of Delhi, Delhi, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 1 (2017), Pagination: 160-167Abstract
Modification of media and illegal production is a big problem now a days because of free availability of digital media. Protection and securing the digital data is a challenge. An Integer Wavelet Transformation (IWT) domain based robust watermarking scheme with Singular Value Decomposition (SVD) and Extreme Learning Machine (ELM) have been proposed and tested on different images. In this proposed scheme, a watermark or logo is embedded in the IWT domain as ownership information with SVD and ELM is trained to learn the relationship between the original coefficient and the watermarked one. This trained ELM is used in the extraction process to extract the embedded logo from the image. Experimental results show that the proposed watermarking scheme is robust against various image attacks like Blurring, Noise, Cropping, Rotation, Sharpening etc. Performance analysis of proposed watermarking scheme is measured with Peak Signal to Noise Ratio (PSNR) and Bit Error Rate (BER).Keywords
IWT, SVD, ELM, PSNR, BER.Full Text
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