4.5 Article

A new DCT-based robust image watermarking method using teaching-learning-Based optimization

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ELSEVIER
DOI: 10.1016/j.jisa.2019.04.001

Keywords

Robust image watermarking; Desert cosine transform (DCT); JPEG YCbCr color space; JPEG Compression; Teaching-Learning-Based optimization (TLBO)

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Despite the passage of more than 20 years of raising the issue of watermarking by Tirkel, the researchers are still seeking to provide an approach more resistant than existing solutions. In this paper we proposed a new watermarking method that works on JPEG-YCbCr color space and the embedding operation is based on the relationships between the DCT coefficients. The JPEG-YCbCr is rescaling of YCbCr color space that has a good robustness against most of the attacks and it used in JPEG image format. Also the relationship between the DCT coefficients is stable against most of the changes in the host image. Therefore, the proposed method has more robustness compared to some other methods. On the other hand, many intelligent optimization methods are in use regarding the nature of the phenomenon simulated by the methods. Teaching-Learning-Based Optimization (TLBO) is a novel method of optimization which has become a hot issue in recent years. The algorithm works on the principle of teaching and learning, where teachers increase the knowledge of students and also the students learn from interaction among themselves. The proposed method uses TLBO which has been applied rarely so far in watermarking algorithms and it can automatically determine the embedding parameters and suitable position for inserting the watermark. Besides, in the object function of TLBO, ensuring higher imperceptibility and also robustness against Median filter and JPEG compression have been considered. According to the experimental results, the imperceptibility of watermarked images is satisfactory, and embedded watermark is extracted successfully even if the watermarked image is distorted by various attacks. (C) 2019 Elsevier Ltd. All rights reserved.

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