博碩士論文 103522013 詳細資訊




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姓名 邱敬淳(Ching-Chun Chiu)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 基於H.264/AVC去區塊濾波器之視訊片段編輯偵測
(Detection of Video Shot Editing by Deblocking Filter of H.264/AVC)
檔案 [Endnote RIS 格式]    [Bibtex 格式]    至系統瀏覽論文 (2018-9-1以後開放)
摘要(中) 本論文提出基於H.264/AVC去區塊濾波器之視訊編輯偵測機制,研究目的在於判斷待測編碼視訊是否曾發生改變視訊內容的操作,例如片段刪除、置換或插入等。考量原始視訊以H.264/AVC進行編碼,而鑑識方取得的待測視訊多也以同樣的格式編碼,當原始編碼視訊經過若干編輯與再次編碼後,可能造成原先GOP(Group of Pictures)中的I畫面轉換成P畫面,我們利用這些畫面所產生的異常編碼情況評估編碼視訊的真實性。
大多數已被提出的竄改視訊偵測方法多利用區塊預測殘差資訊,本研究則採用H.264/AVC中的去區塊濾波器相關訊息,它比現有的方式更難被施予反偵測攻擊。我們將去區塊濾波器中用來判斷4x4區塊邊界執行濾波強度的依據,即邊界強度(Boundary Strength,BS)取出,把每張畫面的BS值以二維圖像建構兩種分佈圖:Prediction Residual Graph (PRG)以及Inter-Prediction Graph (IPG)。為因應各類反偵測或是竄改所造成畫面編碼內容不連續,本論文定義三種畫面分佈不連續狀況,分別為數量、破碎程度以及質心位置不連續。數量不連續通常發生在編碼資訊被更動但仍遵守H.264/AVC正常編碼的情況,而破碎程度及質心位置不連續兩者則較常發生於編碼資訊被改動且可能受到若干進階反偵測攻擊時。若改動區塊數量較多則造成分析圖中發生更多破碎的情況,而改動數量少通常造成分析圖的所謂質心偏移。基於上述狀況,我們使用兩種圖像搭配成三種偵測方法:(1) VRF(Variation of Residual Footprint),即利用PRG改良現有VPF(Variation of Prediction Footprint),以計算數量不連續為主的偵測方法。(2) DOF (Degree Of Fragments),針對IPG中破碎程度不連續的偵測方法。(3) VCF(Variation of Centroid Footprint),計算PRG之質心位置偏移量作為偵測方法。最後,我們估測峰值間距,尋找出現次數最多的間距得到首次編碼的GOP大小,再取得視訊片段編修位置。此外,本研究也以最新的反偵測技術,一個基於改變量化後係數的攻擊方法,來對所提出的基於去區塊濾波器偵測機制進行驗證。實驗結果顯示,不論編碼時使用固定QP(Quantization Parameter)或採用CBR(Constant Bit Rate)編碼,經過反偵測攻擊後的視訊仍然暴露異常情況,證明本研究所提出方法的強健性。
摘要(英) The purpose of this research is to develop a forensic scheme to determine whether an investigated video has been tampered by editing processes, including shot deletion, replacement or insertion, and so on. A detection mechanism based on H.264/AVC de-blocking filter is proposed. Considering that the original video is encoded with H.264/AVC and so is the investigated video, when certain shots in the original encoded video is edited, the re-encoding, may make some I frames in the original GOP (Group of Pictures) be converted into P frames. Such abnormal coding information generated by the tampering operations is employed to assess the authenticity of the investigated video.
Most of the proposed tampering detection methods utilize the information of the coding residuals. This study makes use of the de-blocking filter related information in H.264/AVC, which is more difficult to be attacked by anti-detection method than the existing methods. We extract the Boundary Strength (BS), which is the basis of the de-blocking filter for evaluating the filter strength of 4x4 block boundaries. Two graphs for analysis are formed, i.e., Prediction Residual Graph (PRG) and Inter-Prediction Graph (IPG) in a two-dimensional image. In order to deal with various kinds of anti-detection or tampering operations, the proposed method defines three kinds of discontinuities by analyzing PRG or IPG. Three evaluation methods are thus developed, including (1) VRF (Variation of Residual Footprint), which operates on PRG to improve the existing VPF (Variation of Prediction Footprint), (2) DOF (Degree of Fragments), which processes IPG and (3) VCF (Variation of Centroid Footprint), which calculates the offset of centroid in PRG. Finally, we estimate the distances between the detected peaks and find the distance that occurs most frequently to acquire the original GOP size, followed by the determination of the editing position. Besides, the latest anti-detection technology, an attacking method based on changing the quantized coefficients, is also used to verify the proposed detection mechanism based on the de-blocking filter. Experimental results show that, no matter using the fixed QP (Quantization Parameter) or CBR (Constant Bit Rate) encoding, the video after anti-detection attack still reveals abnormal phenomena, which demonstrate the robustness of the proposed method.
關鍵字(中) ★ H.264/AVC
★ 視訊編修偵測
★ 去區塊濾波器
★ 畫面增刪
關鍵字(英) ★ H.264/AVC
★ video editing
★ de-blocking filter
★ frame insertion/deletion
論文目次 論文摘要 I
Abstract III
誌謝 V
目錄 VI
附圖目錄 VIII
表格目錄 X
第一章 緒論 1
1.1 研究動機 1
1.2 研究貢獻 3
1.3 論文架構 3
第二章 相關研究與文獻探討 4
2.1 偵測方法 4
2.1.1 影片竄改及其偵測方法 4
2.1.2 VPF偵測方法及其優缺點 7
2.2 反偵測方法 9
第三章 提出的方法 13
3.1 異常生成與偵測基礎 13
3.1.1 P畫面預測錯誤 13
3.1.2 De-blocking Filter與BS 15
3.2 竄改與反偵測造成BS分佈不連續 17
3.3 分佈圖與偵測方法 21
3.3.1 分佈圖 21
3.3.2 偵測方法 23
3.4 實例分析與定義影片竄改偵測及竄改處 26
3.4.1 原始GOP與實例分析 26
3.4.2 竄改處找尋 34
第四章 實驗結果 38
4.1 實驗設定 38
4.2 反偵測處理後偵測結果比較 39
4.2 偵測結果分析 41
第五章 結論與未來工作 46
參考文獻 47
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指導教授 蘇柏齊 審核日期 2016-11-14
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