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A dimensionality reduction-based approach for secured color image watermarking

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Abstract

Recently, digital images are widely used in several applications through advanced wearable devices and networks. Despite several benefits of digital images, such as easy distribution, storage, and reproduction, it is difficult to prevent the issue of identity theft, privacy leakage, and ownership conflicts. To solve the above issues, dimensionality reduction-based robust watermarking for color images, supported with suitable encryption, is presented in this article. In this method, principal component analysis (PCA)-based dimensionality reduction is applied to the color carrier image to produce three principal components. The third component with minimum energy is then concealed with a mark image using non-sub-sampled shearlet transform (NSST)-singular value decomposition (SVD)-based watermarking to resolve the ownership issues, if any. In addition, encryption of marked image is done to provide better security and authenticity. The final encrypted image is then stored in a cloud environment for better accessibility. Finally, an experimental and comparative evaluation of the proposed framework justifies its versatility, robustness, and imperceptibility with the best improvement of 47.49 %.

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Data availability

The datasets analyzed during the current study are available online in Refs. (Singh and Kumar 2020; Singh and Singh 2017; Su 2016; Su et al. 2014).

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Funding

This work is supported by Thapar Institute of Engineering and Technology, Patiala, India under SEED Research Grant. A. Anand has received research support from Thapar Institute of Engineering and Technology, Patiala.

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  1. Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Ashima Anand

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  1. Ashima Anand
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Correspondence to Ashima Anand.

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Anand, A. A dimensionality reduction-based approach for secured color image watermarking. Soft Comput 28, 5137–5154 (2024). https://doi.org/10.1007/s00500-023-09233-2

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