ABSTRACT :
Watermarking is one of the most vital digital information hiding technique, which can be used with cryp- tography mechanism for providing more security to digital data. In image watermarking mechanism mostly LSB substitution is used on the cover image for hiding the secret watermark. In this paper, a novel technique based on the matching of bit pairs and symmetric key cryptography is proposed. Pixel bits of original image and encrypted watermark image are arranged in pairs. The pixel bits are represented in pairs following the proposed algorithm, then the encrypted watermark pixel bit pairs are compared with all bit pairs of original image and accordingly the replacement of bit pairs takes place with the respective matched pair assigned number binary equivalent. If no match is found then go for replacing the 0th pair with watermark bits and replace the two LSB with the value of pair number 0. The proposed mechanism shows good quality of watermarked image along with good PSNR values with a good payload. By com- paring the results with some existing algorithms, the proposed scheme shows the valuable results.
EXITING SYSTEM :
In this segment, we offer a brief review related to LSB matching and other mechanisms of LSB. The work in Wu and Tsai (2003) proposed pixel value differencing mechanism in which a pixel value differencing is used to differentiate between edge areas in comparison to smooth areas. Consequently, the payload of the embedded data is higher in edge areas than that of areas of smooth. Recently the authors proposed certain mechanisms combining PVD and LSB replacement for better embedding efficiency (Chang and Tseng, 2004). A number of methods were proposed by combining PVD and LSB replacement mechanisms (Mahjabin et al., 2012; Khodaei and Faez, 2012; Mandal and Das, 2012). In Gutub et al. (2009) the authors proposed a good algorithm on steganography by merging the idea of random pixel manipulation methods and the stego key ones. This mechanism shows good outcomes of hiding capacity with relation to the RGB image pixels. In the paper (Sumathi et al., 2014) a mechanism developed called LSB-MR(Least Significant Bit Matching Revisited). In this method, the embedding process is carried on a cover pixel pair at a time to embed the secret bit pair. The corresponding stego pixel pair can be formed by keeping that cover pixel pair unaltered or by increasing or decreasing the value by one. A function is used here to evaluate the need for alteration to cover pixel values. Practically this mechanism reflected poor embedding rate. To generalize this mechanism a LSB-M(Matching) method was proposed in Li et al. (2009). To enhance the security of both LSB-M and GLSBM, a content adaptive mechanism proposed by the authors (Wang et al., 2010). In Sabeti et al. (2013) the authors proposed a LSB-M adaptive algorithm called complexity based LSB-M in which a complexity region is determined for embedding of data by using an 8-neighborhood of a pixel. The disadvantage of this mechanism was low embedding capacity. In the paper (Tsai et al., 2016) the mechanism based on interpolation, LSB substitution, and histogram shifting. The interpolation process is used to adjust embedding capacity for low distortion of the image, the embedding is then applied using LSB substitution and shifting of histogram mechanism.
DISADVANTAGES OF EXISTING SYSTEM :
1) Less accuracy
2)low Efficiency
PROPOSED SYSTEM :
This segment reflects the proposed method by means of imperceptibility and capacity of data hiding. To judge the performance of the system certain outcomes are assessed with some state of the art mechanisms.
To authenticate the performance of the method, a number of standard grayscale images of size 512 512 and one grayscale watermark of size 32 32 are used. The grayscale watermark image is given in Fig. 4 and the test grayscale images are given in Fig. 6. To proof, the accuracy of the scheme fifteen sample images is taken for illustration. Below we have given the images with results.
The watermark after applying encryption given in Fig. 5 and Fig. 7 shows the watermarked Images.
The encrypted watermark is embedded multiple times within the original grayscale image as per the bit pairs matching using the adaptive bits pair replacement. As the result of embedding, the original image suffers a loss in quality which is calculated by means of some well-known and good quality metrics to check the invisibility of the embedded watermarks for imperceptibility.
ADVANTAGES OF PROPOSED SYSTEM :
1) High accuracy
2)High efficiency
SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10
HARDWARE REQUIREMENTS:
Processor : Core I3
RAM Capacity : 2 GB
Hard Disk : 250 GB
Monitor : 15″ Color
Mouse : 2 or 3 Button Mouse
Key Board : Windows 08/10
