vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff27510a0000006b0f000001001000 Steganography is the art of hiding the fact that communication is taking place, by hiding information in other medium. Many different carrier file formats can be used, but digital images are the most popular because of their frequent use on the Internet. For hiding secret information in images, there exists a large variety of steganographic techniques. The Least Significant Bit (LSB) based approach is a simplest type of steganographic algorithm. In all the existing approaches, the decision of choosing the region within a cover image is performed without considering the relationship between image content and the size of secret message. Thus, the plain regions in the cover will be ruin after data hiding even at a low data rate. Hence choosing the edge region for data hiding will be a solution. Many algorithms are deal with edges in images for data hiding. The Paper 'Edge adaptive image steganography based on LSBMR algorithm' is a LSB steganography presented the results of algorithms on gray-scale images only. This paper presents the results of analyzing the performance of edge adaptive steganography for colored images (JPEG). The algorithms have been slightly modified for colored image implementation and are compared on the basis of evaluation parameters like peak signal noise ratio (PSNR) and mean square error (MSE). This method can select the edge region depending on the length of secret message and difference between two consecutive bits in the cover image. For length of message is short, only small edge regions are utilized while on leaving other region as such. When the data rate increases, more regions can be used adaptively for data hiding by adjusting the parameters. Besides this, the message is encrypted using efficient cryptographic algorithm which further increases the security.
B. Sharmila1 and R. Shanthakumari2
1Erode Builder Educational Trust Institutions, India,2Kongu Engineering College,India
Least Significant Bit(LSB) Based Steganography, Pixel Value Difference (PVD), Data Embedding, Data Extraction, Embedding Unit(EU), Vigenere Table
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 2 , Issue: 3 , Pages: 387-392 )
Date of Publication :
February 2012
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