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High-capacity image hiding scheme based on vector quantization

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Presentation on theme: "High-capacity image hiding scheme based on vector quantization"— Presentation transcript:

1 High-capacity image hiding scheme based on vector quantization
Authors: Yu-Chen Hu Source: Pattern Recognition, Volume 39, Issue 9, September 2006 speaker: Kuo Hua Wang Date: 2006/8/24

2 Outline Introduction The virtual image cryptosystem
The proposed scheme Results Conclusions

3 Introduction Two categories of Image hiding schemes -spatial domain -frequency domain The proposed scheme -LSB technique are employed to cut down the storage cost of indices -Improve the image quality of the stego-image

4 Virtual image cryptosystem(1)
H: host image S: secret image K: H,S partitioned into blocks of k pixels : G,D: Two randomly generated vectors of k-dimensions r: The number of bits use to hide secret image

5 Virtual image cryptosystem(2)
The set of image vectors in H’ is reordered according to the projected values to form the codebook of codewords. After the codebook is generated, the secret image S is now compressed by VQ to generated the indices of the closest codewords in the codebook.

6 The proposed scheme(1) w,h: Host image H and secret images are w × h pixels. sno: Total number of secret images Nc: The size of the VQ codebook k: Vector dimension rs,pk: Two random seeds sk: Secret key RANG: Searching range : Displacement threshold

7 The proposed scheme(2) embed four secret images of512 × 512 pixels into the host image of the same size, 128 codewords is used and each codeword is of 16 pixels. (4×512×512×log2 128)/(16×512× 511)=2. LBG algorithm is used to design the codebook of Nc codewords with the codebook initialization by the randomly selected codewords in the training vectors with random seed rs.

8 The proposed scheme(3) Index compression technique DES
G1: If the same index can be found in its neighbor in the specific range (RANG) G2: If I(x)is quite close to its previous index I(x-1) but not the same. G3: Others

9 The proposed scheme(4) To hide the encrypted secret data into the remaining (h−1) rows of the host image, we need to determine the hiding capacity table (HCT). Two basic rules are used to determine the entries in HCT. First, ECIT should be fairly embedded into each host pixel. Second, the complex pixels should embed more secret bits than that of smooth pixels. The ADD value assigned to each AAD entry is ranged from 1 to rmax A pseudo random number generator with random seed pk is used to generate a serial of random numbers that are used to determine the positions of the pixels that will sequentially be used to embed the encrypted secret data.

10 The proposed scheme(5)

11 The proposed scheme(6) Suppose we want to embed the secret data into the selected pixel h(i, j ) with value 127. Let HCT(i, j ) = 2 and the 2-bit secret data s(i, j) equals (00)

12 Results(1)

13 Results(2)

14 Results(3)

15 Results(3)

16 Conclusions Improved hiding capacity
Two random seeds rs and pk and the secret key sk are used in the proposed scheme The image qualities of the secret images and the stego-images are good for practical applications.


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