Open-Set source camera identification based on envelope of data clustering optimization (EDCO)


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The task of source camera identification is devoted to linking an image to the source camera model and plays a significant role in forensics. Nevertheless, with the ongoing development of new camera models, it is difficult to keep a model database up to date, giving rise to the open-set problem. To deal with this problem, we propose a novel approach based on the envelope of data clustering optimization (EDCO). The new EDCO scheme can identify the camera model regardless of whether or not it is included in the database. The experimental results prove that EDCO efficiently separates unknown source images from known source images and links the query image identified as known with the source camera model. When the dataset is expanded with the new camera model, EDCO only needs to train the new model instead of retraining with all models together, which greatly improves the scalability. Compared with the state of the art, our method can effectively distinguish between images from known and unknown camera models, even in extreme cases. (C) 2021 Elsevier Ltd. All rights reserved.
Source camera identification, Open-Set recognition, Digital image forensics, Image processing, Multimedia security
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