Analysis and Experimental Study of EMD and GEMD Steganographic Methods

The aim of this thesis is to analyze and experimentally study two steganographic methods: Exploiting Modification Direction (EMD) and Generalized Exploiting Modification Direction (GEMD). In the known experiments conducted on EMD and GEMD, some quality metrics like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and the embedding capacity Bit Per Pixel (BPP) are discussed, but implementation important details such as the secret image used, data structures, justification of methods, and the optimal cover images number calculation are not provided. Therefore, in this thesis, the implementation of these methods is explained in details such as the input-output data structures, the justification of the methods and the minimum number of cover images computation are given. The main idea in EMD is that a separate n-pixel group of a cover image is used for embedding of each next digit of (2n+1) -ary k-digit number representation of the next L-bit block from a binary input stream and only one pixel in the n-pixel group could be modified by ±1. In GEMD, L-bit blocks, L=n+1, from the input stream are embedded in the next n-pixel group, and at least one pixel value in each group could be changed by ±1. In the implementation, four grayscale 512×512 secret images, and two cover image sizes, 512×512 and 1024×1024, are used. According to our analysis, for the both cover image sizes results, PSNR of EMD is greater than that of GEMD by 0.06%. For MSE, EMD has less MSE than that of GEMD by 0.5%. On the other hand, GEMD is better than EMD in embedding capacity, BPP is greater by 0.33%. GEMD is also better than EMD in memory and time consumption by 0.006% and 0.06% respectively for the 512x512 cover image size, while for the second size, 1024x1024 by 0.004% and 0.13% respectively. In addition, where each method is compared with different cover image sizes, for both methods, greater cover image size has less time consumption by 0.33% for EMD and by 0.38% for GEMD. For memory consumption, using grater size required more memory for both methods, by 0.02%. For comparison with known experiments with 512×512 cover size, we got the practically the same values for PSNR, MSE, and BPP.