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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36328完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 貝蘇章 | - |
| dc.contributor.author | Dun-Yu Hsiao | en |
| dc.contributor.author | 蕭敦育 | zh_TW |
| dc.date.accessioned | 2021-06-13T07:57:11Z | - |
| dc.date.available | 2008-07-26 | - |
| dc.date.copyright | 2005-07-26 | - |
| dc.date.issued | 2005 | - |
| dc.date.submitted | 2005-07-24 | - |
| dc.identifier.citation | [1]. Marichal, X.; Ma W. Y.; Zhang H. J.; “Blur determination in the compressed domain using DCT information” in Proceedings of International Conference on Image Processing, vol. 2, pp. 386 - 390, 1999
[2]. Elder, J. H.; Zucker, S.W.; “Local scale control for edge detection and blur estimation” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, No. 7, pp. 699 – 716, 1998 [3]. Elder, J. H.; Zucker, S.W.; “Scale space localization, blur, and contour-based image coding“ in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 27 – 34, 1996 [4]. Popescu, A.C.; Farid, H.; “Exposing digital forgeries by detecting traces of re-sampling” in IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 53, No. 2, pp. 758 – 767, 2005 [5]. Lyu, S.; Farid, H.; “How realistic is photorealistic?” in IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 53, No. 2, pp. 845 – 850, 2005 [6]. Popescu, A.C.; Farid, H.; “Statistical Tools for Digital Forensics”, Department of Computer Science at Dartmouth College [7]. Lyu, S.; Farid, H.; “Higher-order Wavelet Statistics and their Application to Digital Forensics” in IEEE Workshop on Statistical Analysis in Computer Vision, 2003 [8]. Farid, H.; “Detecting Digital Forgeries Using Bispectral Analysis”, Perceptual Science Group, MIT, Cambridge, MA 02139 [9]. Popescu, A.C.; Farid, H.; “Exposing Digital Forgeries by Detecting Duplicated Image Regions”, Department of Computer Science, Dartmouth College [10]. Popescu, A.C.; Farid, H.; “Exposing Digital Forgeries in Color Filter Array Interpolated Images” , Department of Computer Science, Dartmouth College [11]. Ng, T. T.; Chang, S. F.; “A model for image splicing” in IEEE International Conference on Image Processing, vol. 2, pp. 1169 – 1172, 2004 [12]. Ng, T. T.; Chang, S. F.; Sun, Q.; “Blind detection of photomontage using higher order statistics” in IEEE Proceedings of International Symposium on Circuits and Systems, vol.5, pp. 688 – 691, 2004 [13]. Ng, T. T.; Chang, S. F.; “A Data Set of Authentic and Spliced Image Blocks“ in ADVENT Technical Report, No. 203-2004-3, Columbia University, Electrical Engineering Department, Columbia University, New York, 2004 [14]. Ng, T. T.; Chang, S. F.; “Blind Detection of Digital Photomontage using Higher Order Statistics “ in ADVENT Technical Report, No. 203-2004-3, Columbia University, Electrical Engineering Department, Columbia University, New York, 2004 [15]. Fridrich, J.; Soukal, D.; Lukáš, J.; “Detection of Copy-Move Forgery in Digital Images”, Department of Electrical and Computer Engineering, Department of Computer Science [16]. Kerlow, I. V.; The Art of 3-D Computer Animation and Effects, 3rd ed., John Wiley, ISBN: 0471430366 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/36328 | - |
| dc.description.abstract | 你可曾自己修改不滿意的數位照片？如果有，那你就算接觸過數位影像的編修了。隨著科技進步，電腦能提供的運算能力越來越強大，伴隨方便、容易上手卻又擁有強大功能的數位影像軟體，有經驗的使用者就能夠將數位多媒體資料轉變成為他們所想要的形式，而以影像方式呈現的媒體為其大宗。隨之而來且日益重要的是如何去偵測數位影像編修合成竄改的問題。
在大多數的時候，數位影像的修改是不容易被發現的，編修過的痕跡往往會被其作者盡力消去，避免其容易被分辨出來。然而，對影像的後製過程幾乎都會留下些蹤跡，雖然對人的肉眼而言難以察覺。基於這個想法，這篇論文中提出了幾個方式以及想法來應付並偵測數位影像的編修痕跡，但是並不藉由廣為人知的數位浮水印技巧。在各種偵測方式中，其有效性以及結果將會於相對應的章節中 做詳細的探討。 | zh_TW |
| dc.description.abstract | Have you ever edited some unsatisfied digital photographs of yours? If the answer is yes, then you have made some digital tampering. With powerful computer and mighty software, seasoned users could turn digital media into what they want. The detection of digital tampering has
become a crucial problem. In most of the time, digital tampering is not perceptible by human; however, some traces of digital tampering may be left in the media during the process. Based on this idea, several detection methods are proposed in this thesis to against various common digital tampering without any help of embedded information such as the well-known atermarking technique. Effectiveness and results will be presented in each method, robustness will also be discussed. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T07:57:11Z (GMT). No. of bitstreams: 1
ntu-94-R92942028-1.pdf: 7829488 bytes, checksum: e4c55410a00f07c5f7094421340e7a16 (MD5) Previous issue date: 2005 | en |
| dc.description.tableofcontents | Introduction to Digital Image Tampering Frauds 1
Section I: Topic Background 3 Chapter 1 All about Digital Image Tampering 3 1.1 Categories of image manipulation 3 1.2 Discussions about embedded framework 13 1.3 Earlier studies 14 Section II: Various detection schemes to specific manipulation 17 Chapter 2 Detection in Digital Editing Involving Re-sampling 19 2.1 The re-sampling procedure 20 2.2 Detecting re-sampling 25 2.3 Summary 29 Chapter 3 Exposing Blur in Digital Forensic 31 3.1 Blur estimation 33 3.1.1 Digital image tampering detection using blur estimation —the frequency domain approach 46 3.1.2 Digital image tampering detection using blur estimation —the spatial domain approach 47 3.2 Results of blur estimation 48 3.2.1 Results of blur estimation performed on ordinary blurred images 48 3.2.2 Digital image tampering detection results from the frequency domain approach 53 3.2.3 Digital image tampering detection results from the spatial domain approach 57 3.3 Error discussions 63 3.4 Other applications 64 3.5 Summary 64 Chapter 4 Analysis of Computer Assisted Graphics 65 4.1 The proposed system model of computer graphics and photography 68 4.2 The observation of inconsistency in computer-generated object 69 4.3 Global blur estimation on computer-generated images 76 4.4 Photorealistic images? Or artworks 79 Chapter 5 Conclusion 81 Appendix 87 The expectation maximization algorithm and Farid’s approach for exposing digital forensics 87 Reference 95 Source Image 97 | - |
| dc.language.iso | en | - |
| dc.title | 數位影像編修竄改及其偵測 | zh_TW |
| dc.title | Digital Image Tampering Synthesis and Identification | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 93-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 鍾國亮,黃仲陵,陳永昌 | - |
| dc.subject.keyword | 數,位影像,編修,竄改, | zh_TW |
| dc.subject.keyword | digital image,tampering,manipulation,fraud,forensic,forgery,doctoring, | en |
| dc.relation.page | 98 | - |
| dc.rights.note | 有償授權 | - |
| dc.date.accepted | 2005-07-24 | - |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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