Bulletin of Electrical Engineering and Informatics Vol. 13, No. 4, August 2024, pp. 2537~2546 ISSN: 2302-9285, DOI: 10.11591/eei.v13i4.7884  2537 Journal homepage: http://beei.org Enhancing quality measurement for visible and invisible watermarking based on M-SVD and DCT Kusnawi 1 , Joang Ipmawati 2 , Dwi Puji Prabowo 3 1 Department of Informatics, Faculty of Computer Science, AMIKOM University, Yogyakarta, Indonesia 2 Department of Computer Engineering, Faculty of Information Technology, Nahdlatul Ulama University Yogyakarta, Yogyakarta, Indonesia 3 Department of Visual Communication Desain, Faculty of Computer Science, University of Dian Nuswantoro, Semarang, Indonesia Article Info ABSTRACT Article history: Received Nov 15, 2023 Revised Jan 29, 2024 Accepted Feb 24, 2024 This study introduces an advanced method for evaluating non-blind watermarking quality, leveraging both visible and invisible watermarking techniques grounded in principles of discrete cosine transform (DCT) and modified singular value decomposition (M-SVD). The primary focus is to refine the assessment process of watermarked images by integrating M- SVD, known for its efficacy in measuring image quality and watermarking performance. Results from the M-SVD implementation exhibit a striking resemblance to the original images. The mean squared error (MSE) values for watermarked images range from 0.0003 to 0.0168, while peak signal-to- noise ratio (PSNR) values vary between 42.52 dB and 82.72 dB. These outcomes underscore the potential of DCT and M-SVD techniques in bolstering watermarking processes, especially in invisible watermarking contexts. Keywords: Discrete cosine transform Invisible watermarking Multi-singular value decomposition Quality measurement Visible watermarking This is an open access article under the CC BY-SA license. Corresponding Author: Kusnawi Department of Informatics, Faculty of Computer Science, AMIKOM University Ring Road Utara, Condong Catur, Sleman, Yogyakarta, 55283, Indonesia Email: khusnawi@amikom.ac.id 1. INTRODUCTION Image quality is a crucial aspect in the digital world, influencing the effectiveness and visual impression conveyed [1]-[4]. In an era of advancing technology, the threat to image integrity has escalated due to the ease of manipulating images using sophisticated editing tools. Moreover, as images are increasingly susceptible to unauthorized alterations, ensuring their integrity, and authenticity becomes paramount [5]-[7]. Digital watermarking allows for the insertion of imperceptible watermarks into images as unique identifiers or authentication proofs, safeguarding images against unauthorized modifications, and ensuring their authenticity [8]. In setting the context for this research, it is imperative to delineate the prevailing landscape and state-of-the-art advancements within the domain of digital watermarking and image integrity [9]. Over recent years, the proliferation of digital media and the advent of sophisticated image editing tools have engendered a heightened vulnerability to image tampering and unauthorized usage [10]. Consequently, the quest for robust, reliable, and imperceptible watermarking techniques has intensified, necessitating innovative methodologies that seamlessly integrate with existing image processing frameworks [11], [12]. The evolution of watermarking strategies has witnessed a paradigm shift towards invisible watermarking solutions, wherein the emphasis lies not only on embedding ownership or authentication data covertly but also on preserving the inherent quality and visual fidelity of the images [13]. Concurrently, advancements in quality measurement metrics have emerged as pivotal determinants, facilitating rigorous evaluation, and validation of watermarking techniques [14].