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논문 기본 정보

자료유형
학술저널
저자정보
Jinwoo Kang (Sangmyung University) Sang-ug Kang (Sangmyung University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.10 No.6
발행연도
2021.12
수록면
447 - 454 (8page)
DOI
10.5573/IEIESPC.2021.10.6.447

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초록· 키워드

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In this study, we propose an image copyright protection technology to prevent analog hole attacks using a deep object detection network. Instead of applying a virtual fence to the whole image, only a region of copyright is protected with fences. The region of copyright interest is called the protection zone and is generated by merging bounding boxes found with a YOLO network. The protection zone is adjusted to satisfy the fence generation rules, and then the virtual fence is finally applied. The main goal of this study is to attenuate the image degradation caused by virtual fences while preserving copyright protection capability. Since the virtual fence method uses the afterimage effect of the human visual system, it is necessary to generate images perceived by a human eye at every moment in order to calculate the objective image quality compared to the original unprotected image. Perceived images are generated at every 0.001 seconds using the mathematical model of the afterimage effect. The protection zone is found using object bounding boxes detected using a YOLO deep neural network. We applied the proposed method to four animation images, and the simulation results show that it achieves image quality that is about 3dB better than that of other methods.

목차

Abstract
1. Introduction
2. Related Works
3. The Proposed Method
4. Simulation Results
5. Conclusion
References

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