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Author :Ji-Hwei Horng (洪集輝) Professor National Quemoy University

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1 Author :Ji-Hwei Horng (洪集輝) Professor National Quemoy University
Hiding Secret Image in Absolute Moment Block Truncation Code By Using a Block-Selection Scheme Author :Ji-Hwei Horng (洪集輝) Professor National Quemoy University

2 AMBTC(Absolute moment block truncation coding)
Divide the image into 4 ×4, Calculate the block average : = Calculate the absolute value of the retained momentum of the block : α Calculate the high and low mean value of the reconstruction order: l = h = Average=100 High mean value = 160; Low mean value = 64

3 The (7, 4) Hamming code to hide secret data into the AMBTC image
An image vector of 7 digits can be used to hide 3 digits of secret data by change a single digit. The parity check matrix H is multiplied with the image vector to obtain a 3 digits vector. This vector is then taking exclusive-OR with the 3 digits secret data to get the 3 digits syndrome. This syndrome indicates which digit in the image vector to be change. Fig. 1 The coding process of the (7, 4) Hamming code Fig. 2 The decoding process of the (7, 4) Hamming code

4 The Block Selection Scheme
The cover image Lena , the image size is 512x512, the use of AMBTC calculated average difference value of the high and low average coding block, resulting in a 128x128 difference blocks to difference compressed image histogram . Quantity Lena image using AMBTC Difference of value Calculate block difference histogram

5 Select image dithering
Try to embed the secret image into the cover image. Actually, the size of the secret image is 256 × 256, because the size of the corresponding cover image is 512 × 512. In order to increase the embedding capacity, we quantize the grayscale secret image into a binary image. Dithering is applied to enhance the visual quality of binary images. Binary images using dithering technique

6 Block Selection The embedded binary image: 256x256 bits Hiding capacity of a 4x4 image block: 3x2 bits The total number of blocks required: (256x256) / (3x2) = blocks The total number of blocks in the cover image: (512/4)x(512/4)=128x128=16384 blocks Hiding Efficiency: 10923/16384 = 67%

7 Block Selection Select the candidate blocks in the increasing order of difference value until we get accumulated blocks in total. The final value of in-block difference is the threshold Bth of selection. In most cases, there are multiple candidates with the same threshold value Bth. For the candidate blocks at the threshold difference, we select them in the raster scan order on the block array until we get the enough accumulated number and record the coordinates (bx, by) of the final block.

8 Secret image embedding and extraction
To hide the secret image, the coordinates of the final block (bx, by) are first encoded into two binary 8-bits, and two zeros are added to form two 9-bits elements and merge into one 18-bits. The 18-bits is embedded in the first three reserved blocks in the cover image. A secret image of size 256x256 is arranged to form a number of bits of To embed = 65538/6 blocks, two 0 bits will have to be attached. Each image block is divided into an upper group and a lower group Incoming seven pixels in the upper and lower groups

9 Secret image embedding and extraction (continued)
Extraction process: The secret image extracting process is in the reverse order. We decode the first three blocks to find the coordinates of the final block (bx, by) and find its in-block difference by using its high-value and low value. Then, we scan the blocks of the whole cover image to find the blocks that meet the embedding criterion and decode the secret data.

10 The Experimental Results
In our experiment, the secret image of size 256x256 is shown in Fig. 1. To condense the information required to send, it is quantized to binary image and enhanced by the dithering technique. The resulting image to transmit is also shown in the figure. To compare with other methods, the cover image is a Lena image of size 512x512. The AMBTC compressed image is shown in Fig2. The stego images produced by using the Chang’s method and our method are also given. . (a) AMBTC compressed image (b) The Chang’s stego image Fig. 1 (c) The proposed stego image Fig2

11 The Experimental Results(continued)
Test both algorithms on the other images(Fig. 3). The PSNR for different test images are given in Table I. In all test images, the PSNR of the stego images produced by our algorithm are very close to the cover images. Fig.3

12 The Experimental Results(continued)
In addition, the secret image is attempted as a color image, and the hidden image RGB is separately subjected to the dithering technique, as shown in Fig.4. The cover image is a color Lena image with a size of 512x512 and its hidden color image is as shown in Figure.5. The comparison result is shown in Table 2. (a) AMBTC compressed image (b) The Chang’s stego image (c) The proposed stego image Fig.4 Fig.5

13 Conclusions In this paper, we try to embed a secret image into a AMBTC compressed cover image by using the (7,4) Hamming code method. The secret image is quantized and dithered to get a condensed image with an acceptable visual quality. Then, we leverage 67% of the cover image’s hiding capacity to embed the secret image. The proposed block selection scheme successfully improved the PSNR value of the stego image and therefore could hardly be detected. Experiments show that our method works equally well in the color image application.

14 References [1]Edward J. Delp and O. Robert Mitchell, “Image Compression Using Block Truncation Coding,” IEEE Trans. Communications, pp , Vol. COM-27, No. 9, SEPTEMBER 1979. [2]Maximo D. Lema and O. Robert Mitchell, “Absolute Moment Block Truncation Coding and Its Application to Color Images,” IEEE Trans. Communications, pp , Vol. COM-32, No. 10, OCTOBER 1984. [3]J.C. Chuang and C.C. Chang, “Using a simple and fast image compression algorithm to hide secret information,” International Journal of Computers & Applications, Vol. 28, No. 4, pp , 2006. [4]C.C. Chang, Y.J. Liu, and S.T. Nguyen, Hiding Secret Information in Block Truncation Code Using Dynamic Programming Strategy, Proceedings of 6th International Graphic and Image Processing, vol. 9443, Beijing, China, 2014. [S]. Lin and D. J. Costello, Jr., Error Control Coding, Fundamentals and Applications, Englewood Cliffs, NJ: Prentice-Hall, 1983. [6] McAndrew, Wang, and Tseng, Introduction to Digital Image Processing with MATLAB, Thomson Learning, 2004.


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