Forthcoming and Online First Articles

International Journal of Critical Computer-Based Systems

International Journal of Critical Computer-Based Systems (IJCCBS)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Critical Computer-Based Systems (1 paper in press)

Regular Issues

  • An Enhanced Digital Image Watermarking Technique using DWT-HD-SVD and Deep Convolutional Neural Network   Order a copy of this article
    by Manish Rai, Sachin Goyal, Mahesh Pawar 
    Abstract: This paper proposes a novel image watermarking model, which combines discrete wavelet transform (DWT), Hessenberg decomposition (HD), singular value decomposition (SVD)-based deep convolutional neural networks (D-CNN) technique to explore the subjective and objective quality of the images. Initially, the source and cover image are preprocessed using random sampling techniques. During the process of embedding a watermark image, the cover image is decomposed into a number of sub-bands using the DWT process and the resulting coefficients are fed into the HD process. In continuation to it, the source image is operated on the SVD simultaneously and finally, the cover image is embedded into the source image by the attack-defending process. The probability of data loss during the watermarking extraction process and this issue is postulated by the D-CNN technique that explores the denoising process on the extracted watermarked images. The experimental results show that the proposed method has a good trade-off between robustness and invisibility even for the watermarks with multiple sizes.
    Keywords: watermarking; discrete wavelet transform; DWT; singular value decomposition; SVD; deep convolutional neural networks; D-CNN; watermarking embedding; extraction process.
    DOI: 10.1504/IJCCBS.2022.10050956
     

 

Return to top