(Regular Paper) 22 5, 2017 9 (JBE Vol. 22, No. 5, September 2017) https://doi.org/10.5909/jbe.2017.22.5.643 ISSN 2287-9137 (Online) ISSN 1226-7953 (Print) a), a), b) A Statistical Approach for Improving the Embedding Capacity of Block Matching based Image Steganography Jaeyoung Kim a), Hanhoon Park a), and Jong-Il Park b), 3.,..,, k-. PSNR. Abstract Steganography is one of information hiding technologies and discriminated from cryptography in that it focuses on avoiding the existence the hidden information from being detected by third parties, rather than protecting it from being decoded. In this paper, as an image steganography method which uses images as media, we propose a new block matching method that embeds information into the discrete wavelet transform (DWT) domain. The proposed method, based on a statistical analysis, reduces loss of embedding capacity due to inequable use of candidate blocks. It works in such a way that computes the variance of each candidate block, preserves candidate blocks with high frequency components while reducing candidate blocks with low frequency components by compressing them exploiting the k-means clustering algorithm. Compared with the previous block matching method, the proposed method can reconstruct secret images with similar PSNRs while embedding higher-capacity information. Keyword : Image steganography, block matching, discrete wavelet transform, high capacity, block variance, statistical analysis Copyright 2017 Korean Institute of Broadcast and Media Engineers. All rights reserved. This is an Open-Access article distributed under the terms of the Creative Commons BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and not altered.
(JBE Vol. 22, No. 5, September 2017).., [2,3]. (steganography) [1]... LSB(least significant bits) [4]. PVD [5], PVD PVD [6]. Fresnel [7], DCT [8], DWT [9-11]. a) (Department of Electronic Engineering, Pukyong National University) b) (Department of Computer and Software, Hanyang University) Corresponding Author : (Hanhoon Park) E-mail: hanhoon_park@pknu.ac.kr Tel: +82-51-629-6225 ORCID: http://orcid.org/0000-0002-6968-4565. Manuscript received July 11, 2017; Revised August 28, 2017; Accepted August 28, 2017. DWT [12]. PSNR.. 2 [12] - [13], 3. 4, 5.. DWT [12] -. 1. DWT(discrete wavelet transform) DWT. 2 2D-DWT. 1D-DWT 1 (b) 1.. 1 (b) 1D-DWT 2D-DWT 1 (c) 4
(a) (b) (c) 1. (a), 1D-DWT (b), 2D-DWT (c) Fig. 1. The origin image (a), 1D-DWT image (b) and 2D-DWT image (c) LL, LH, HL, HH. LL LH, HL, HH,,. 1, 2. DWT,. 2. DWT. 100% /. DWT [12]. step 1 : 2D-DWT LL, LH, HL, HH. step 2 : LL. step 3 :. step 4 : LL ( ). step 5 : ( ) step 4. 1 3. log LSB LH, HL, HH. 3. -. 4.
(JBE Vol. 22, No. 5, September 2017).. 5.... ( 1 ). [12]. 2 4.875, 1.375. -. 1. DWT LL 1. Table 1. Ratio of unused blocks Previous block matching method [12] cover secret baboon boat lena goldhill einstein average baboon 0.5305 0.5876 0.5037 0.5439 boat 0.1760 0.3379 0.2007 0.3162 lena 0.2410 0.1931 0.1995 0.2722 goldhill 0.1262 0.2632 0.3767 0.2722 einstein 0.1597 0.2429 0.3015 0.1953 0.3020 2. Fig. 2. Pixel and deviation values of low frequency blocks with a size of
.. LL.,, 6.,. LL LL ( ) LL - k. k. LL. 7. log log 1, 8, LL. LH, HL, HH LSB. 2. DWT LL. LH, HL, HH.. 5 log + 9 log + 9.... [12], -. bpp(bits per a pixel)( 8 ). bpp. PSNR(peak signal to noise ratio) 9. / log log
648 방송공학회논문지 제22권 제5호, 2017년 9월 (JBE Vol. 22, No. 5, September 2017), (9) log. 1. 기존 블록 매칭 방법과 제안된 방법의 PSNR과 bpp비교 기존 볼록 매칭 방법 과 제안된 방법의 삽입 용량, 스테 [12] 고 영상의 은닉성 복원률을 비교하기 위해서 크 기의 8비트, 1채널 영상 5개(baboon.bmp, boat.bmp, lena.bmp, goldhill.bmp, einstein.bmp)를 커버와 비밀 영상으 로 사용한다(그림 3 참조). 실험은 크기로 영상을 분할하여 삽입을 하였고 군 집화 알고리즘의 =16, 삽입의 대체 비트 수는 2비트 로 하였다. 표 2의 결과는 제안된 방법과 기존 블록 매칭 방법의 복원된 비밀 영상의 PSNR에 대해서 보여준다. 제 안된 방법의 경우 PSNR이 1dB정도 적지만 일반적으로 3. 실험에 사용된 영상 Fig. 3. The images used for the experiment 그림 2. 복원된 비밀 영상의 PSNR 비교 Table 2. Comparison of PSNRs of the reconstructed secret images 표 =16 Proposed method Previous block matching method[12] (a) cover secret baboon boat lena goldhill einstein baboon boat lena goldhill einstein baboon 24.9024 24.7332 25.1387 24.7003 25.4958 25.085 25.4293 24.9051 (b) boat 29.6571 30.4375 30.3957 30.2617 30.5114 31.4592 31.2489 30.8846 lena 31.8239 32.2235 32.7187 32.8924 33.0515 33.7779 33.7855 33.6874 goldhill 30.6321 31.2385 31.2196 31.5576 31.8763 33.0638 32.83 32.6512 (c) 4. 커버 영상 (a), 비밀 영상 (b), 스테고 영상 (c), 복원 영상 (d) Fig. 4. a cover image (a), a secret image (b), a stego image (c) and a restored image (d) 그림 einstein 31.6769 31.8963 32.3236 32.2747 33.1625 33.8743 34.2738 34.1571 avg PSNR 30.1352 31.2605 (d)
3. PSNR Table 3. Comparison of PSNRs of the stego images =16 cover secret baboon boat lena goldhill einstein avg PSNR baboon 41.5226 41.0724 42.0329 42.0946 Proposed method Previous block matching method [12] boat 44.187 45.5445 46.1556 44.9641 lena 46.4636 46.8735 46.8713 47.0435 goldhill 46.2895 46.6819 46.8397 46.8911 einstein 46.3235 46.6211 46.7303 46.607 baboon 40.6875 41.3176 40.499 40.495 boat 44.9529 44.4863 44.4685 44.4567 lena 46.2412 46.1669 46.1737 46.1766 goldhill 46.1495 46.1294 46.108 46.0726 einstein 46.1579 46.1398 46.1349 46.1333 45.3905 44.7574 4. bpp Table 4. Comparison of bpp and insertion bits =16 cover secret baboon boat lena goldhill einstein Proposed method Previous block matching method [12] baboon 0.94 0.91 0.91 0.89 246043 239526 240170 233716 boat 1.0579 0.9159 0.9211 0.8935 277328 240092 241472 234230 lena 1.0788 0.9497 0.9362 0.9012 282806 248948 245420 236240 goldhill 1.1257 0.9697 0.9402 0.9127 295106 254219 246477 239253 einstein 1.1148 0.9773 0.9456 0.9711 292238 256202 247874 254570 all images avg bpp avg insertion bits 0.96 251658 1.25 1.25 327680 327680 PSNR 30dB (human visual system). baboon PSNR 25dB baboon PSNR ( 2 ). ( 4 ). 1dB PSNR ( 3 ). bpp. bpp 1.25. bpp 0.96 0.96 bpp 77%. baboon PSNR bpp 0.1 ( 4 ). 2. k PSNR bpp PSNR bpp. 5 ( )
(JBE Vol. 22, No. 5, September 2017) 5. PSNR, bpp, Table 5. Average PSNR, bpp and insertion bits of the proposed method according to the number of clusters restored images average PSNR stego images average PSNR average bpp average insertion bits 2 29.2487 46.1627 0.82 214958 4 29.6149 45.8916 0.83 217580 8 29.9399 45.5558 0.92 241172 16 30.1352 45.3905 0.96 251658 32 30.3223 45.4098 1.01 264765 2. 5 PSNR bpp PSNR bpp. baboon 4 PSNR 30dB PSNR bpp 4. 3 5 PSNR...,. PSNR PSNR PSNR. k-. baboon.. (References) [1] J. Zollner, H. Federrath, H. Klimant, A. Pfitzmann, R Piotraschke, A. Westfeld, G. Wicke, and G. Wolf, Modeling the Security of Steganographic Systems, Proc. of Workshop on Information Hiding, pp. 345-355, 1988. [2] H. Kim, Theoretical Background and Detection Technique of Steganography, Journal of the Korea Information Security, Vol. 12, No. 1, pp. 34-47, 2002. [3] K. Jung, J. Lee, and K. Yoo, Steganography on Android Smart Devices, Journal of the Institute of Electronics and Information Engineers, Vol. 52, No. 4, pp. 100-105, 2015. [4] D. C. Wu and W. H. T, A Steganographic Method for Images by Pixel-Value Differencing, Pattern Recognition Letters, Vol. 24, pp. 1613-1626, 2003. [5] J. Kim, H. Park, and J-I. Park, PVD Image Steganography with Locally-fixed Number of Embedding Bits, Journal of Broadcast Engineering, Vol. 22, No. 3, pp. 350-365, 2017. [6] S. Ji, A Study of Optimal Image Steganography Based on LSB
Techniques, Journal of the Korea Industrial Information Systems Research, Vol. 20, No. 3, pp. 29-36, 2015. [7] Y. Lee, Y. Seo, and D. Kim, Hologram Watermarking using Fresnel Diffraction Model, Proc. of the Korea Society of Broadcast Engineers Conference, Vol. 19, No. 5, pp. 606-615, 2014. [8] W. Sohn and L. N. T. dung, A Blind Watermarking Scheme using Singular Vector Based on DWT/RDWT/SVD, Journal of Broadcast Engineering, Vol. 21, No. 2, pp. 149-156, 2016. [9] Y. Lee, Y. Seo, and D. Kim, A Robust Blind Watermarking for Digital Image using DWT According to Its Resolution, Journal of Broadcast Engineering, Vol. 20, No. 6, pp. 888-900, 2015. [10] S. Youssef, A. A. elfarag, and R. Raouf, A Robust Steganography Model using Wavelet-based Block-partition Modification, International Journal of Computer Science & Information Technology, Vol. 3, No. 4, pp. 15-28, 2011. [11] S. Singh and T. J. Siddiqui, A Security Enhanced Robust Steganography Algorithm for Data Hiding, International Journal of Computer Science Issues, Vol. 9, No. 1, pp. 131-139, 2012. [12] J. Kim, H. Park, and J-I. Park, Image Steganography Based on Block Matching in DWT Domain, Proc. of BMSB, Cagliary, Italy, 2017. [13] T. Kanungo, D. Mount, N. Netanyahu, C. Piako, R. Silverman, and A. Wu, An Efficient -means Clustering Algorithm: Analysis and Implementation, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 24, No. 7, pp. 881-892, 2000. - 2012 : - 2016 ~ : - ORCID : http://orcid.org/0000-0003-2348-3626 - : - 2000 : - 2002 : - 2007 : - 2008 ~ 2011 : NHK - 2012 ~ : - ORCID : http://orcid.org/0000-0002-6968-4565 - :,, 3 / - 1987 : - 1989 : - 1995 : - 1992 ~ 1994 : NHK - 1995 ~ 1996 : - 1996 ~ 1999 : ATR - 1999 ~ : - ORCID : http://orcid.org/0000-0003-1000-4067 - :,, 3,