Fast digital watermarking of uncompressed colored images using bidirectional extreme learning machine
Ankit Rajpal, Anurag Kumar Mishra, Rajni Bala · 2017
Development of fast watermarking schemes for all multimedia objects is crucial to the present day research in information security. Besides speed of execution minimizing the trade-off between visual quality and robustness is another important requirement of this research domain. In view of this, a newly developed single layer feedforward network (SLFN) commonly known as Bidirectional Extreme Learning Machine (B-ELM) is employed to carry out watermark embedding and extraction from four colored images. The results show that the B-ELM technique outperforms the previously employed ELM technique for this purpose. It is concluded that visual quality and robustness trade-off is minimized and real time targets are achieved. Thus, the proposed scheme is found to be suitable for developing video watermarking applications.