Fast digital watermarking of uncompressed colored images using bidirectional extreme learning machine

Abstract

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.