Quantum neural network for image watermarking

Abstract

In this paper, we investigate the application of Quantum neural network (QNN) to the document image watermarking problem. The method first divides the document into some weight-invariant partitions in the spatial domain. For better performance, we then reduce the watermarking problem to a classification problem, and use the Quantum neural network to solve it. QNN, characterized by the principles of quantum computing including concepts of qubits, superposition and entanglement of states, is a relatively new type of neural networks. Owning to the power of Quantum search, QNN is considered to have at least the same computational power as classical networks. We test the performance of QNN and the experimental results indicate the soundness of our method. © Springer-Verlag 2004.