Blind Detection for Additive Embedding Using Underdetermined ICA

 

Hafiz Malik, Ashfaq Khokhar, Rashid Ansari, and Marco Salvemini

Department of Electrical and Computer Engineering, University of Illinois At Chicago, Chicago, Illinois, USA

 

Abstract

This paper presents an efficient blind watermark detection scheme for additive embedding (AE) based on underdetermined independent component analysis (ICA) framework. The proposed detector assumes that the host signal and the watermark obey non-Gaussian distributions and watermark embedding follows AE model. The proposed blind watermark detector employs blind source separation (BSS) for underdetermined mixtures to estimate watermark. Simulation results are presented showing that the proposed detector performs significantly better than existing blind detectors operating without suppressing the host signal interference at the detector.

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