Lifting Wavelet Transform based Fast Watermarking of Video Summaries using Extreme Learning Machine

Abstract

In this paper, we present a robust semi-blind video watermarking scheme in lifting wavelet transform (LWT) domain using Extreme Learning Machine (ELM). In this scheme, first the static video summary is generated using extraction of color features from video frames. Second, the frames comprised of video summary are watermarked in LWT domain. To develop a robust and real time watermarking scheme, a fast Single hidden Layer Feedforward Neural Network (SLFN) known as ELM is used for watermark embedding and extraction. To evaluate the performance of the present scheme, several signal processing attacks are applied to each watermarked frame. Experimental evidence shows that the proposed scheme is robust against selected attacks. Due to fastprocessing of frames, the proposed scheme is also found to be suitable for real time watermarking of video.