Establishment of Robust Source Camera Identification Technologies for Digital Images
| Project/Area Number |
26330152
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Information security
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| Research Institution | The University of Aizu (2015-2016)
Tokyo University of Agriculture and Technology (2014) |
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Principal Investigator |
Tomioka Yoichi 会津大学, コンピュータ理工学部, 准教授 (10574072)
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| Co-Investigator(Kenkyū-buntansha) |
北澤 仁志 東京農工大学, 工学(系)研究科(研究院), 教授 (60345329)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | カメラ識別 / クラスタPRNUノイズ / シーンコンテンツ / 拡大率推定 / PRNUノイズ / FAST / BRIEF / 周期的補間アーティファクト / スキャナ識別 / 精度評価手法 / 経年変化 / クラスタペア / PRNU |
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| Outline of Final Research Achievements |
In this research, we aim to establish source camera identification to identify a camera which took digital images using Photo Response Non-Uniformity (PRNU) Noise. We proposed a theoretical framework for accuracy evaluation of camera identification. To improve the accuracy of camera identification, we proposed a novel camera identification method based on the matching of image feature points on PRNU noise image, PRNU estimation method considering the effects of scene contents, and scaleing factor estimation method for a resized image. Moreover, in scanner identification, we showed the effects of the number and background color of scanned images, and we also showed the effects of aged deterioration.
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Report
(4 results)
Research Products
(6 results)
