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Erschienen in:
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2021 | OriginalPaper | Buchkapitel

53. Robust Image Watermarking Using DWT and Artificial Neural Network Techniques

verfasst von : Anoop Kumar Chaturvedi, Piyush Kumar Shukla, Ravindra Tiwari, Vijay Kumar Yadav, Sachin Tiwari, Vikas Sakalle

Erschienen in: Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Verlag: Springer Singapore

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Abstract

Content in this digital world plays an important role which is available in the form of text, image, video, etc. So protecting this from unauthorized access is an important issue. Hence researcher works, in this field from last few decades and proposed number of methods. The proposed work offers a robust and fast algorithm for embedding watermark in an image. In the proposed work, DWT feature was used where embedding was done in LL band. Security of data was improved by Inverse S-order before embedding data. Embedded data is transformed into training vector for neural network model, while corresponding watermark bit is desired output. Embedded data is passing in neural network for learning which gives a corresponding watermark bit. Sothis involvement of neural network for watermark detection increases the robustness of the work. Real set of images was utilized for performing the experiment. Evaluation parameters show that proposed work has enhances PSNR, SNR, NC parameters as compared to existing methods.

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Metadaten
Titel
Robust Image Watermarking Using DWT and Artificial Neural Network Techniques
verfasst von
Anoop Kumar Chaturvedi
Piyush Kumar Shukla
Ravindra Tiwari
Vijay Kumar Yadav
Sachin Tiwari
Vikas Sakalle
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Print ISBN: 978-981-15-7532-7

Electronic ISBN: 978-981-15-7533-4

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-15-7533-4_53

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