Title :
Decision of image watermarking strength based on artificial neural-networks
Author :
Shi-Chun, Mei ; Ren-Hou, Li ; Hong-Mei, Dang ; Yun-Kuan, Wang
Author_Institution :
Syst. Eng. Inst., Xi´´an Jiaotong Univ., China
Abstract :
Digital watermarking is a new technique for digital multimedia copyright protection. The robustness and the imperceptibility are the basic requirements of the digital watermark. The key factor that affects both the robustness and the imperceptibility of the digital watermark is the watermarking strength. In this paper, artificial neural network (ANN) is used to model human visual system (HVS) and an ANN-based image-adaptive method for deciding watermarking strength for image DCT coefficients is presented. The experimental results show that the method can increase the watermarking strength so that the robustness of digital watermark is enhanced and that the method has very good adaptability.
Keywords :
binary sequences; discrete cosine transforms; feedforward neural nets; image coding; iterative methods; learning (artificial intelligence); transform coding; watermarking; DCT coefficients; Levenberg-Marquardt algorithm; Sigmoid function; artificial neural network; digital multimedia copyright protection; digital watermarking; feedforward neural network; human visual system; image watermarking strength decision; image-adaptive method; imperceptibility; pseudo random binary sequence; robustness; Artificial neural networks; Copyright protection; Discrete cosine transforms; Frequency; Humans; Image coding; Robustness; Systems engineering and theory; Visual system; Watermarking;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1201930