Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/98260
DC FieldValueLanguage
dc.contributor沈肇基zh_TW
dc.contributorJau-Ji Shenen_US
dc.contributor.author陳昭如zh_TW
dc.contributor.authorZhao-Ru Chenen_US
dc.contributor.other資訊管理學系所zh_TW
dc.date2018zh_TW
dc.date.accessioned2019-03-22T06:43:42Z-
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dc.identifier.urihttp://hdl.handle.net/11455/98260-
dc.description.abstract近年來,隨著網際網路的發展快速,影像處理技術也蓬勃發展,現在在智慧型手機上也可以輕鬆修改影像。但是正因為如此,有心人士想要蓄意竄改影像的機會就會大幅增加。本研究提出了可自我回復的脆弱型浮水印影像認證法,並且分為基於區塊和基於像素的檢測法。在區塊檢測法中,從每個區塊中產生認證資訊以及利用區塊平均值來產生回復資訊,並且根據區塊大小的不同,來調整要認證資訊及回復資訊的數量。透過實驗結果可以發現,因為當檢測到被竄改像素時,則該像素所屬的區塊會整個被標記為被竄改區塊,因此若區塊劃分的較小,則檢測的誤判率FPR則會較小。而像素檢測法則當檢測到被竄改像素值時僅將該像素標記為被竄改,因此誤判率會比區塊檢測法來得少。與現有的方法相比,本方法在較高的竄改率下,仍可以有較好的竄改檢測及回復的性能。zh_TW
dc.description.abstractIn recent years, with the rapid development of the Internet as well as image processing technology, digital images on smart phones can be easily modified. Thus, criminal image modification has skyrocketed. In this paper, we propose an effective self-embedding authentication watermarking scheme for tampered image detection and recovery. The proposed method is classified into block-wise and pixel-wise detections. In block-wise detection, the authentication information and the recovery information are generated from each block and its mean value, respectively. According to the size of a block, the number of the authentication information and recovery information are adjusted. When the tampered pixel is detected, the corresponding block is marked; therefore, if the size of the block is small, the false positive rate (FPR) will be low. In pixel-wise detection, when the tampered pixel is detected, only the corresponding pixel area is marked. Therefore, the FPR will be lower than that the block-wise detection. The experimental results demonstrate that the proposed method is effective, and an accurate tamper detection and high-quality recovery can be realized even in highly tampered images.en_US
dc.description.tableofcontents摘要 i Abstract ii 目錄 iii 圖目錄 v 表目錄 vii 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機與目的 2 1.3 研究架構 3 第二章 文獻探討 4 2.1 符號定義 4 2.2 針對數位影像的新型可逆式影像認證技術(2014) 4 2.3 使用自適應藏入規則的影像竄改檢測及回復法(2016) 5 2.4 基於Hilbert Curve映射的改進式可逆式影像認證法(2016) 6 2.5 基於DCT的有效自我藏入及回復影像認證法(2016) 7 2.6 文獻特點比較 8 第三章 研究方法 10 3.1 符號定義 10 3.2 基於「區塊」檢測的影像認證技術 11 3.2.1 產生浮水印並藏入影像 11 3.2.2 竄改檢測及自我回復 13 3.3 基於「像素」檢測的影像認證技術 15 3.3.1 產生浮水印並藏入影像 15 3.3.2 竄改檢測及自我回復 18 第四章 實驗結果 20 4.1 實驗環境及實驗用圖 20 4.2 影像驗證竄改實驗 22 4.3 與其他方法之比較 30 第五章 結論與未來展望 33 5.1 結論 33 5.2 未來展望 33 參考文獻 34zh_TW
dc.language.isozh_TWzh_TW
dc.rights同意授權瀏覽/列印電子全文服務,2021-08-14起公開。zh_TW
dc.subject影像認證技術zh_TW
dc.subject竄改檢測zh_TW
dc.subject脆弱型浮水印zh_TW
dc.subjectImage authentication schemeen_US
dc.subjectTamper detectionen_US
dc.subjectFragile watermarking methoden_US
dc.title有效的自嵌入認證水印用於圖像竄改檢測與恢復zh_TW
dc.titleEffective Self-Embedding Authentication Watermarking for Image Tampered Detection and Recoveryen_US
dc.typethesis and dissertationen_US
dc.date.paperformatopenaccess2021-08-14zh_TW
dc.date.openaccess2021-08-14-
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