Quality Improvement for Invisible Watermarking using Singular Value Decomposition and Discrete Cosine Transform

Danang Wahyu Utomo; Christy Atika Sari; Folasade Olubusola Isinkaye

doi:10.30812/matrik.v23i3.3744

Danang Wahyu Utomo Universitas Dian Nusnwantoro, Semarang, Indonesia http://orcid.org/0000-0001-7758-951X
Christy Atika Sari Universitas Dian Nusnwantoro, Semarang, Indonesia http://orcid.org/0000-0002-7296-5210
Folasade Olubusola Isinkaye Ekiti State University, Ado-Ekiti, Nigeria http://orcid.org/0000-0001-5012-7446

DOI: https://doi.org/10.30812/matrik.v23i3.3744

Keywords: Discrete Cosine Transform, Invisible Watermarking, Quality Improvement, Singular Value Decomposition

Abstract

Image watermarking is a sophisticated method often used to assert ownership and ensure the integrity of digital images. This research aimed to propose and evaluate an advanced watermarking technique that utilizes a combination of singular value decomposition methodology and discrete cosine transformation to embed the Dian Nuswantoro University symbol as proof of ownership into digital images. Specific goals included optimizing the embedding process to ensure high fidelity of the embedded watermark and evaluating the fuzziness of the watermark to maintain the visual quality of the watermarked image. The methods used in this research were singular value decomposition and discrete cosine transformation, which are implemented because of their complementary strengths. Singular value decomposition offers robustness and stability, while discrete cosine transformation provides efficient frequency domain transformation, thereby increasing the overall effectiveness of the watermarking process. The results of this study showed the efficacy of the Lena image technique in gray scale having a mean square error of 0.0001, a high peak signal-to-noise ratio of 89.13 decibels (dB), a universal quality index of 0.9945, and a similarity index structural of 0.999. These findings confirmed that the proposed approach maintains image quality while providing watermarking resistance. In conclusion, this research contributed a new watermarking technique designed to verify institutional ownership in digital images, specifically benefiting Dian Nuswantoro University. It showed significant potential for wider application in digital rights management.

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Author Biographies

Christy Atika Sari, Universitas Dian Nusnwantoro, Semarang, Indonesia

Christy Atika Sari received the M.CS double degree for master in Informatic Engineering from Dian Nuswantoro University and University Teknikal Malaysia Melaka (UTeM) in 2012. She is currently active as author in international journals and confrences scopus indexed. She also awarded as best author and best paper in national and intenational confrence in 2019 and 2020 respectively and awarded from KEMENDIKBUDRISTEK (Ministry of Research and Technology of the Republic of Indonesia) as the Indonesian top 50 best researchers in 2020. Now, she served as editor and reviewer for several international reputable journal and TPC of several IEEE Confrences. She currently as senior lecturer in intelligent systems and and continue to develop the research field image processing, machine learning, deep learning, data security, and data hiding. She can be contacted at email: christy.atika.sari@dsn.dinus.ac.id.

Folasade Olubusola Isinkaye, Ekiti State University, Ado-Ekiti, Nigeria

Folasade Olubusola Isinkaye received a Bachelor of Science degree in Computer Science from the Ondo State University, Ado-Ekiti, (now EKSU) Nigeria. Her Master of Science and PhD degrees were obtained in Computer Science from the University of Ibadan, Nigeria. She is a Senior Lecturer at the Department of Computer Science, Ekiti State University, Ado-Ekiti, Nigeria. She was also the Ag. Head of the Department of Computer Science, Ekiti State University from 2020-2022. She is a member of professional bodies which include the Computer Professional [Registration Council of Nigeria (CPN)] and the Association for Computing Machinery (ACM). She was a visiting PhD scholar at the Laboratory of Knowledge Management, Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Italy. Also, a Postdoctoral research fellow at the Department of Computer Science & Information Technology, Sol Plaatje University, Kimberley, South Africa. Her research interests include recommender systems, information systems, and machine learning. She can be contacted at: folasade.isinkaye@eksu.edu.ng.

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