Image Authentication Using Block Truncation Coding in Lifting Wavelet Domain

Author:

Bhardwaj Anuj1,Verma Vivek Singh2,Gupta Sandesh3

Affiliation:

1. Department of Mathematics, Jaypee Institute of Information Technology, Noida, Uttar Pradesh 201309, India

2. Department of Information Technology, Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh 201009, India

3. Department of Computer Science and Engineering, University Institute of Engineering and Technology, CSJM University, Kanpur, Uttar Pradesh 208024, India

Abstract

Image watermarking is one of the most accepted solutions protecting image authenticity. The method presented in this paper not only provides the desired outcome also efficient in terms of memory requirements and preserving image characteristics. This scheme effectively utilizes the concepts of block truncation coding (BTC) and lifting wavelet transform (LWT). The BTC method is applied to observe the binary watermark image corresponding to its gray-scale image. Whereas, the LWT is incorporated to transform the cover image from spatial coordinates to corresponding transform coordinates. In this, a quantization-based approach for watermark bit embedding is applied. And, the extraction of binary watermark data from the attacked watermarked image is based on adaptive thresholding. To show the effectiveness of the proposed scheme, the experiment over different benchmark images is performed. The experimental results and the comparison with state-of-the-art schemes depict not only the good imperceptibility but also high robustness against various attacks.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on mechanism of joint-coding imaging based on generative adversarial neural network;Optics and Lasers in Engineering;2023-12

2. TMCIH: Perceptual Robust Image Hashing with Transformer-based Multi-layer Constraints;Proceedings of the 2023 ACM Workshop on Information Hiding and Multimedia Security;2023-06-28

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