臺灣博碩士論文加值系統

本研究中，我們提出了一種於二元影像裡的高容量資訊隱藏應用方法，在二元影像當中只有2種顏色(黑色與白色)，所以是難以在沒有察覺的狀況之下嵌入資料，而安全性與資訊嵌入量是我們一直討論與權衡的問題。在嵌入秘密資訊之前，我們先使用亂數產生器將資料重新打亂，可增加資訊安全性。在一個M×N的掩護影像中，將掩護影像劃分為(2k+1)×(2k+1)不重疊的區塊，其中k=1,2,3…，(M或N較小者)。我們將不重疊的母區塊再分割成四個重疊的(k+1)×(k+1)子區塊，並跳過所有全黑或全白的(2k+1)×(2k+1)區塊。我們在重疊的(k+1)×(k+1)的區塊中，將四個角落區塊與母區塊(2k+1)×(2k+1)中心像素施作XOR運算，在每個(k+1)×(k+1)區塊可中嵌入k^2個位元，總共可藏4×k^2。整個主掩護圖像可以嵌入4×k^2×M/(2k+1)×N/(2k+1)位元。
提取的方法是檢測每個(k+1)×(k+1)四個角落的子區塊和(2k+1)×(2k+1)母區塊中心像素之間XOR運算。收集所有嵌入的位元，然後還原成原來的順序。我們想要選擇的方法，可能會影響嵌入量與影像的不可查覺性。實驗結果表明該方法提供了大的嵌入容量維持不可察覺和掩護影像的低失真率。

In this paper, we propose a high capacity data hiding method applying in binary images. Since a binary image has only two colors, black or white, it is hard to hide data imperceptible. The capacities and imperception are always in a trade-off problem. Before embedding we shuffle the secret data by a pseudo-random number generator to keep more secure. We divide the host image into several non-overlapping(2k+1)×(2k+1)sub-blocks in an M by N host image as many as possible, where k=1,2,3,…,or min (M,N). Then we partition each sub-block into four overlapping(k+1)×(k+1)sub-blocks. We skip the all blacks or all whites in each(2k+1)×(2k+1)sub-blocks. We consider all four(k+1)×(k+1)sub-blocks to check the XOR between the non-overlapping parts and center pixel of the(2k+1)×(2k+1)sub-block, it embed k^2bits in each(k+1)×(k+1)sub-block, totally are4×k^2. The entire host image can be embedded 4× k^2×M/(2k+1)×N/(2k+1)bits. The extraction way is simply to test the XOR between center pixel with their non-overlapping part of each sub-block. All embedding bits are collected and shuffled back to the original order. The adaptive means the partitioning sub-block may affect the capacities and imperception that we want to select. The experimental results show that the method provides the large embedding capacity and keeps imperceptible and reveal the host image lossless.

目錄
中文摘要I
英文摘要III
致謝V
目錄VI
表目錄VIII
圖目錄IX
第一章序論01
1.1研究背景與動機01
1.2研究目的02
1.3論文架構02
第二章文獻回顧04
2.1資訊隱藏04
2.2文獻探討05
第三章本文提出的方法11
3.1入規則與方法13
3.2嵌入流程與演算法16
3.3嵌入範例20
3.4提取規則與方法23
3.5提取流程與演算法23
3.6提取範例26
第四章實驗結果27
第五章結論與未來工作44
參考文獻45

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