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A Study of Data Hiding Algorithms for Binary Images with Low Distortion and High Capacity
|關鍵字:||Steganography;資訊隱藏;binary image;low distortion;high capacity;黑白影像;低失真;高容量||出版社:||資訊科學與工程學系||引用:||[Chan2004a] C. K. Chan and L. M. Cheng, “Hiding data in images by simple LSB substitution,” Pattern Recognition, vol. 37, pp. 469-474, March 2004. [Chan2004b] C. C. Chang and H. W. Tseng, “A steganographic method for digital images using side match,” Pattern Recognition Letters, vol.25, no. 12, pp. 1431-1437, September 2004. [Chan2008] C. C. Chang, Y. P. Hsieh, and C. H. Lin, “Sharing secrets in stego images with authentication,” Pattern Recognition, vol. 41, no. 10, pp. 3130-3137, October 2008. [Frid2001] J. Fridrich, M. Goljan M, and R. Du, “Reliable detection of LSB steganography in color and grayscale images,” in Proceedings of ACM Workshop on Multimedia and Security, pp. 27-30. 2001. [Frid2006a] J. Fridrich, M. Goljan, and D. 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本論文基於數位黑白影像資訊隱藏技術在低失真性與高隱藏量的不同需求上，提出二個黑白影像資訊隱藏演算法。第一個演算法為「低失真資訊隱藏」演算法，包含三個步驟。首先，我們將掩護黑白影像切割成若干個具有3x3像素的子區塊。對每個子區塊的中心像素，我們提出一種簡單又有效率的可變動性評分機制，來評定該像素之可變動性程度。我們逐一檢視所有的子區塊。在檢視時，我們以子區塊中心點像素為基準，對其周圍的8個鄰居像素進行可變動性評分。若中心點像素與它附近鄰居像素的黑白點有較多的差別時，則我們稱此像素為可變動像素，並給予較高的分數。其次，我們利用 Arnold 轉換，將黑白影像擾亂成為雜訊影像，直到每個子區塊中至少存在一個以上的可變動像素。最後，我們提出一種創新的資訊隱藏技術來嵌入秘密訊息。我們取3個子影像區塊，每個子區塊內含8x8像素做為隱藏的單位。每單位我們可藏入3個位元的秘密訊息，但只修改單位內至多2個子區塊內所含的1個可變動像素。實驗結果顯示：偽裝影像平均修改率僅為每單位0.333位元，遠小於現存方法所需的平均每單位0.5位元之修改率。本演算法所產生的偽裝影像，具有低失真性，人類眼睛無法察覺其中藏有秘密訊息；演算法也具備盲擷取之特性，無需原始掩護影像即可擷取秘密訊息。
我們所提的第二個演算法為「高容量資訊隱藏」演算法，包含二個步驟。首先，我們仍使用 Arnold 轉換擾亂掩護黑白影像，並且將擾亂後的掩護黑白影像切割成為3x3像素的子區塊。接著，我們計算每個子區塊可變動像素的個數，這些可變動像素包含「白色可變動」像素，亦即原始為白色像像素但可藏入資訊後變為黑色像素；反之，可變動像素也包含「黑色可變動」像素。這些可變動像素之總數代表每個子區塊至少能隱藏的位元數。我們從 Arnold 轉換作像素擾亂所能允許的最大轉換次數中，求出單一子區塊至少能隱藏的位元數。依照此數值，我們提出一種新的資訊隱藏嵌入方式，選取適合的子區塊數構成一個嵌入單位，將秘密訊息嵌入這些子區塊內。實驗結果顯示：使用本演算法，每個子區塊至少可以藏入2個位元以上的秘密訊息，此亦使得每張原始掩護影像至少可以提昇2倍以上的隱藏量。本演算法也具備盲擷取之特性，無需原始掩護影像即可擷取秘密訊息。
最後，由於每張原始掩護影像特性不同，故每區塊擁有可變動像素之個數亦相異。當掩護影像經 Arnold 轉換做像素擾亂以及最佳可變動點評估後發現，但某個子區塊僅有一個可變動點時，我們選取2個子區塊做為嵌入的單位，來嵌入秘密訊息。實驗結果顯示：使用新的方法，每個單位可嵌入3個位元的秘密訊息，使得每個子區塊擁有平均1.5個位元的隱藏量，進一步提升整體的隱藏量。這個新的方法也擁有低失真的特性，以人類視覺靈敏度而言，無法察覺其中藏有秘密訊息。此法也具備盲擷取的特性，無需原始掩護影像即可擷取秘密訊息。
In this thesis, we propose two novel steganographic algorithms for binary images. The first algorithm is capable of significantly reducing the visual artifacts caused by secret data embedding. Our new scheme includes three parts. Firstly, the cover image represented by a binary sequence of 0 or 1 pixel values is subdivided into blocks of sub-images. For each block we introduce a simple yet efficient scheme to estimate a pixel's “flippable value” by examining its neighboring pixels. We give high “flippable value” to a pixel where its neighboring pixels are much different from the current pixel value being examined. Secondly, we utilize the Arnold transform to shuffle the binary image into a noise image. The transformation is conducted several times until each block of sub-image contains at least one pixel with “flippable value”, which indicates that this block of sub-image is feasible to embed, at least, a bit of secret message by flipping the corresponding pixel value. Finally, we present a novel data embedding technique, which employs three blocks of sub-image as a basic embedding unit. This technique ensures the basic unit conveying 3 bits of secret message by flipping at most two pixels with “flippable values” on any two blocks of sub-image. Experimental results show that the stego image produced by our scheme is imperceptible to the human eyes. Comparing to the existing schemes, our method produces the least image distortion, being 0.333 changes per pixel. Besides, our scheme belongs to the blind extraction where the secret data can be extracted without referring to the cover image.
The second algorithm we propose is capable of greatly increasing the embedding capacity for a binary image. First, we utilize the Arnold transform again to shuffle the binary image and subdivide the image into a number of blocks, each of which represents a sub-image. Then, we evaluate each block accordingly to compute numbers of flippable pixels available in the examined block. As a result, we can determine the minimal number of flippable pixels when observing all blocks of sub-image. Finally, referring to the minimal number we can derive a basic embedding unit which groups together a specific number of blocks for data embedding. Once the basic embedding unit is available, we employ the same embedding technique proposed in our first algorithm to embed secret message, enabling to significantly reduce the pixel variation. Experimental results show that our algorithm can convey 2 bits of secret message at each block of sub-image, which has twice the embedding capacity than our counterpart.
Furthermore, we extend our algorithm to consider a particular case when there is only one flippable pixel in a specific block of sub-image, while other blocks of sub-image have at least two flippable pixels. Surely, the capacity is restricted by the block with only one flippable pixel. Under this circumstance, we group two blocks together as the basic embedding unit for secret message embedding. This scheme ensures one basic unit conveying 3 bits of secret message, achieving the capacity of 1.5 bits per block of sub-image. The stego image demonstrates insignificant distortion, imperctable to human visual system. The scheme belongs to the blind extraction where the secret data can be extracted without referring to the cover image.
In conclusion, we propose two novel steganographic algorithms for binary images. Experimental results verify the adventages of our algorithms in providing low distortion and high capacity manners for binary image steganography.
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