From announce at list.ipol.im Thu Apr 4 10:54:31 2024 From: announce at list.ipol.im (announcements about the IPOL journal) Date: Thu, 4 Apr 2024 10:54:31 +0200 Subject: [IPOL announce] new article: Image Forgery Detection Based on Noise Inspection: Analysis and Refinement of the Noisesniffer Method Message-ID: A new article is available in IPOL: https://www.ipol.im/pub/art/2024/462/ Marina Gardella, Pablo Mus?, Miguel Colom, and Jean-Michel Morel, Image Forgery Detection Based on Noise Inspection: Analysis and Refinement of the Noisesniffer Method, Image Processing On Line, 14 (2024), pp. 86?115. https://doi.org/10.5201/ipol.2024.462 Abstract Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of its operations leaves traces on the noise model which enable forgery detection through noise analysis. In this article, we describe the Noisesniffer method [Gardella et al., Noisesniffer: a Fully Automatic Image Forgery Detector Based on Noise Analysis, IEEE International Workshop on Biometrics and Forensics, 2021]. This method estimates for each image a background stochastic model which makes it possible to detect local noise anomalies characterized by their number of false alarms. We improve on the original formulation of the method by introducing a region-growing algorithm to detect local deviations from the background model. Results show that the proposed method outperforms the previous version as well as the state of the art.