Quality of Passive Image Authentication Scheme Based On Scale Space Detectors

Quality of Passive Image Authentication Scheme Based On Scale Space Detectors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quality of Passive Image Authentication Scheme Based On Scale Space Detectors Manaf Ali, Maher Hasan, Ihsan Rasheed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8005868/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The passive image authentication approach represents the backbone of image forensic schemes. In this approach, the forger copies a specific region of an image and then pastes it on the same image. This type of forgery attacks the integrity, secrecy, and authentication of digital images. Feature and block-based techniques are considered the backbone of passive image authentication schemes. The feature-based technique relies on feature detectors to detect the significant key points of the source image where Scale Space Detectors are represented the most important detectors in this technique. These are broken down into Linear Scale Space (LSS), Non-linear Scale Space (NSS), and Curvature Scale Space (CSS). In this paper, we proposed a passive image forensic approach based on scale space detectors. These detectors are the SIFT technique as LSS detector, KAZE technique as the NSS detector, and the MSER technique as CSS detector. We adopted the MLESAC filter as a false positive filter to remove undesired results. Many comparisons have been made between these detectors to extract the efficiency, robustness, and quality of each one. The results show that the running time of the passive scheme based on CSS detector is less than NSS and LSS detectors. The CSS detector is more robust against simple and complex attacks such as brightness, smoothing, and geometric transformation attacks in terms of TPR and FPR. Scale Space Detector SIFT KAZE MSER MLESAC Image Forensic Scheme Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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