An adaptive data hiding method is proposed that encapsulates forbidden zone data hiding in order to improve the robustness of watermark under the premise of ensuring the subjective quality of host video and the invisibility of watermark. The algorithm based on human visual masking characteristics calculates each block's variance and energy and then selects the range of forbidden zone and the embedding strength according to two above values. This method is tested with H.264/AVC compression and strong common signal processing attacks, such as Gaussian filtering, to compare with the original algorithm. The simulation results indicate that the proposed method is more robust against attacks such as noise and compression and can be successfully utilized in video data hiding applications.

http://ieeexplore.ieee.org/iel5/6269386/6291367/06291460.pdf

An adaptive video watermarking algorithm

The recognition accuracy of the traditional biometric secure system is often influenced by the environment and physiological,and it leads to the development of the multimodal biometric systems.This paper presents a multi-modal biometric recognition system based on face and iris feature level fusion.Face and iris texture feature extraction is adopted Center-Symmetric Local Binary Pattern(CS-LBP) operators,the feature vectors that are extracted from face and iris are integrated linearly to form a mixed feature vector,and then Adaboost algorithm is used to select and aggregate the effective features from the mixed feature vector to build the strong classifier.Experimental results show that the system has better robustness than the mono-modal system.

Gao Zhi-ying

Papers

Face and Iris Fusion Recognition Based on Adaboost