Work place: Department of Computer engineering, Tongmyong University, Busan, South Korea
E-mail: indranth@tu.ac.kr
Website:
Research Interests:
Biography
Dr. Indranath Chatterjee is working as a Professor in the Department of Computer Engineering at Tongmyong University, Busan, South Korea. He received his Ph. D. in Computational Neuroscience from the Department of Computer Science, University of Delhi, Delhi, India. His research areas include Computational Neuroscience, Schizophrenia, Medical Imaging, fMRI, and Machine learning. He has authored and edited 8 books on Computer Science and Neuroscience published by renowned international publishers. To date, he has published numerous research papers in international journals and conferences. He is a recipient of various global awards on neuroscience. He is currently serving as a Chief Section Editor of a few renowned international journals and serving as a member of the Advisory board and Editorial board of various international journals and Open-Science organizations worldwide. He is presently working on several projects of government & non-government organizations such as PI/co-PI, related to medical imaging and machine learning for a broader societal impact, in collaboration with several universities globally. He is an active professional member of the Association of Computing Machinery (ACM, USA), Organization of Human Brain Mapping (OHBM, USA), Federations of European Neuroscience Society (FENS, Belgium), Association for Clinical Neurology and Mental Health (ACNM, India), and International Neuroinformatics Coordinating Facility (INCF, Sweden).
By Rajeev Kumar Kshitiz Singh Jainath Yadav Ajay Kumar Indranath Chatterjee
DOI: https://doi.org/10.5815/ijcnis.2025.01.05, Pub. Date: 8 Feb. 2025
The critical challenge with the continuously increasing number of Internet users is copying and duplication, which has caused content integrity and protection. To manage and secure the signals from unauthorized consumers of digital content, we require certain procedures. Digital watermarking scheme on vowel-based approach can address these problems. Thus, we can provide a robust and secure method that solves the issues of copyright, illegal intentional or unintentional modification. In this paper, we have proposed vowel-based speech watermarking techniques using the FFT method with the help of the Min algorithm. We observe that the proposed FFT-based watermarking scheme provides better results in comparison to the existing methods.
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