臺灣博碩士論文加值系統

本論文提出一個使用機密資料切割技術(secret data division)與像素差值(pixel value differencing)為基礎，並搭配模數運算(modulus operation)改善偽裝影像品質的資料隱藏方法。
在資料隱藏(Steganography)之中，隨著藏入資料的增加，對原始影像(cover-image)所造成的失真程度也會越來越嚴重。因此，如果考慮到藏入容量，就得犧牲影像品質；如果顧慮到影像品質，藏入的資料卻又相對減少。在本論文中，我們基於機密資料切割技術與像素差值的概念，在不降低藏入容量的情況下，利用切割的技術減少藏入資料時所造成的失真，並且搭配模數運算藏入資料，藉此提升偽裝影像(stego-image)的品質。如此一來，我們可以在維持一定水準影像品質的前提之下，藏入更多的資料量。
首先，我們先將原始影像切割成若干個互不重疊的區塊，而每一個區塊是由兩個相鄰像素所構成的。藉由計算區塊內兩個像素之間的差值，決定該區塊可藏入的資料量。接著我們將欲藏入區塊中的機密資料(secret data)依照適當的方式切割成兩部分，並且利用模數運算將切割後的機密資料，分別藏入區塊內的兩個像素之中。透過機密資料的切割與模數運算這兩個動作，來提升偽裝影像的品質。
實驗結果部分，藉由統計分析發現，和其他一樣以像素差值為基礎的資料隱藏方法比較後，我們的方法在像素均方差(mean squared error)部分有較佳的表現，證明我們提出的方法確實能有效縮小藏入資料時所造成的失真。而在影像實驗結果方面，在不降低藏入容量的前提下，我們所提出的方法確實能有效提升藏完資料後的偽裝影像品質，相較於其他方法，我們提出的方法在偽裝影像品質部分擁有較小的標準差，這表示我們所提出的方法不易受不同影像性質的影響，適用於更多類型的影像之中。

We propose a steganographic method which is using secret data division and pixel value differencing in this study. It can increase the image quality of the stego-image.
In the filed of steganography, hiding a lot of secret data into the cover-image will cause serious distortion. In other words, the hiding capacity is limited by maintaining the image quality. In this study, we proposed a method using separating techniques and pixel value differencing to solve this problem. By our proposed method, we obtain better effect on the image quality without making any sacrifices for the hiding capacity.
Firstly, we divide the cover-image into several non-overlapping blocks, and each block is composed of two contiguous pixels. We calculate the number of hidden bits based on the difference of these two pixels in a block. The secret data is separated into two parts. We use modulus operation to embed these two parts of secret data into the two pixels, respectively. By separating the secret data and modulus operation, we can reduce the distortion and increase the image quality of the stego-image.
In the experiment result, by computing the statistics of mean squared error, our proposed method has better performance than other methods which are also based on pixel value differencing. It proves that our proposed method can reduce the distortion indeed. Besides, our proposed method can increase the image quality of the stego-image without making any sacrifices. Comparing with others method, our proposed method has more stable performance of the image quality of stego-image than other methods. It means that our proposed method is suitable for more different kinds of images than other methods.

目錄
第一章、緒論 1
1.1 研究背景 1
1.2 資訊隱藏技術介紹 6
1.3 資料隱藏的應用與重要性 9
1.4 研究動機與目的 10
1.5 論文架構 11
第二章、相關文獻 15
2.1 MF 16
2.2 PVD 18
2.3 PVDLSB 20
第三章、方法描述 25
3.1 藏入程序 26
3.1.1 低階層 27
3.1.2 高階層 31
3.2 擷取程序 33
3.2.1 低階層 34
3.2.2 高階層 34
第四章、方法分析與實驗結果 39
4.1 統計分析 40
4.2 影像實驗 42
第五章、結論 55
參考文獻 56



圖目錄
圖 1. 資料隱藏技術的分類 12
圖 2. 數位浮水印 12
圖 3. 灰階影像 13
圖 4. 像素值10的二進位表示法 13
圖 5. LSB交換法 14
圖 6. 範圍表 23
圖 7. 範圍表的階層區分 24
圖 8. 系統流程圖 36
圖 9. Zig-Zag之區塊切割方式 37
圖 10. 不同切割方式的範圍表 38
圖 11. PVD與SDDPVD之MSE曲線圖 44
圖 12. PVDLSB與SDDPVD之MSE曲線圖 44
圖 13. PVD與SDDPVD，在子範圍 之MSE比較 46
圖 14. PVD與SDDPVD，在子範圍 之MSE比較 46
圖 15. PVD與SDDPVD，在子範圍 之MSE比較 47
圖 16. PVD與SDDPVD，在子範圍 之MSE比較 47
圖 17. PVD與SDDPVD，在子範圍 之MSE比較 48
圖 18. PVD與SDDPVD，在子範圍 之MSE比較 48
圖 19. PVDLSB與SDDPVD，在子範圍 之MSE比較 49
圖 20. PVDLSB與SDDPVD，在子範圍 之MSE比較 49
圖 21. PVDLSB與SDDPVD，在子範圍 之MSE比較 50
圖 22. PVDLSB與SDDPVD，在子範圍 之MSE比較 50
圖 23. PVDLSB與SDDPVD，在子範圍 之MSE比較 51
圖 24. 實驗原始影像 52



表目錄
表 1. PVD與提出的方法之MSE統計分析表 45
表 2. PVDLSB與提出的方法之MSE統計分析表 45
表 3. PVD與提出的方法之藏入容量與PSNR比較表 53
表 4. PVDLSB與提出的方法之藏入容量與PSNR比較表 53
表 5. PVD、PVDLSB與提出的方法之標準差比較表 54

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