This paper illustrates the various performance evaluation parameters of image steganography techniques. The performance of a steganographic technique can be rated by three parameters; (i) hiding capacity, (ii) distortion measure and (iii) security. The hiding capacity means the maximum amount of information that can be hidden in an image. It can also be represented as the number of bits per pixel. The distortion is measured by using various metrics like mean square error, root mean square error, PSNR, quality index, correlation, structural similarity index etc. Each of these metrics can be represented mathematically. The security can be evaluated by testing the steganography technique with the steganalysis schemes like pixel difference histogram analysis, RS analysis etc. All these metrics are illustrated with mathematical equations. Finally, some future directions are also highlighted at the end of the paper.

To protect from pixel difference histogram (PDH) analysis and RS analysis, two hybrid image steganography techniques by appropriate combination of LSB substitution, pixel value differencing (PVD), and exploiting modification directions (EMD) have been proposed in this paper. The cover image is traversed in raster scan order and partitioned into blocks. The first technique operates on 2 × 2 pixel blocks and the second technique operates on 3 × 3 pixel blocks. For each block, the average pixel value difference, d, is calculated. If d value is greater than 15, the block is in an edge area, so a combination of LSB substitution and PVD is applied. If d value is less than or equal to 15, the block is in a smooth area, so a combination of LSB substitution and EMD is applied. Each of these two techniques exists in two variants (Type 1 and Type 2) with respect to two different range tables. The hiding capacities and PSNR of both the techniques are found to be improved. The results from experiments prove that PDH analysis and RS analysis cannot detect these proposed techniques.

Digital Image Steganography based on Seven Way Pixel Value Differencing

The traditional pixel value differencing (PVD) steganographical schemes are easily detected by pixel difference histogram (PDH) analysis. This problem could be addressed by adding two tricks: (i) utilizing horizontal, vertical, and diagonal edges and (ii) using adaptive quantization ranges. This paper presents an adaptive PVD technique using 6-pixel blocks. There are two variants. The proposed adaptive PVD for 2×3-pixel blocks is known as variant 1, and the proposed adaptive PVD for 3×2-pixel blocks is known as variant 2. For every block in variant 1, the four corner pixels are used to hide data bits using the middle column pixels for detecting the horizontal and diagonal edges. Similarly, for every block in variant 2, the four corner pixels are used to hide data bits using the middle row pixels for detecting the vertical and diagonal edges. The quantization ranges are adaptive and are calculated using the correlation of the two middle column/row pixels with the four corner pixels. The technique performs better as compared to the existing adaptive PVD techniques by possessing higher hiding capacity and lesser distortion. Furthermore, it has been proven that the PDH steganalysis and RS steganalysis cannot detect this proposed technique.

Images transmitted through internet can be easily tampered by the available image editing tools. This article proposes a Hamming code based watermarking approach for tamper localization and correction of images. The original image is divided into various blocks with 8 consecutive pixels. The 64 bits of the 8 pixels are arranged into an 8 × 8 matrix of bits. A modified (7,4) Hamming code (MHC) is applied on first 7 most significant bits (MSBs) of each row of the matrix. The first 4 MSBs are data bits. The next 3 bits are redundant bits. The watermark bits are calculated from the 4 MSBs and stored in 3 redundant bits. Furthermore, the column parity for the first 7 columns of the 8 × 8 matrix is computed and embedded in the least significant bits (LSBs) of the 7 rows. Thereafter the column parity of the first 7 bits of 8th column is stored in 8th bit location of 8th column. This technique can detect 1-bit error or 2-bit error if it occurs in one of the 8 pixels of the block. Experimental outcomes prove that this proposed scheme maintains 4.0 bits per pixel with 36.94 dB peak signal-to-noise ratio (PSNR) and 0.9781 structural similarity (SSIM).