Advances in Physics Theories and Applications www.iiste.org ISSN 2224-719X (Paper) ISSN 2225-0638 (Online) Vol 3, 2012 9 Compression Technique Using DCT & Fractal Compression – A Survey R M Goudar 1 * Priya Pise 2* 1. Dept Of Computer , Maharashtra Academy Of Engg Alandi (D) ,Pune. 2. Dept Of IT , Indira College Of Engg , Parandwadi ,Tal- Maval ,Pune * E-mail of the corresponding author: rmgoudar66@gmail.com;priya.pise@gmail.com Abstract Steganography differs from digital watermarking because both the information and the very existence of the information are hidden. In the beginning, the fractal image compression method is used to compress the secret image, and then we encrypt this compressed data by DES.The Existing Steganographic approaches are unable to handle the Subterfuge attack i.e, they cannot deal with the opponents not only detects a message ,but also render it useless, or even worse, modify it to opponent favor. The advantage of BCBS is the decoding can be operated without access to the cover image and it also detects if the message has been tampered without using any extra error correction. To improve the imperceptibility of the BCBS, DCT is used in combination to transfer stego-image from spatial domain to the frequency domain. The hiding capacity of the information is improved by introducing Fractal Compression and the security is enhanced using by encrypting stego-image using DES. Keywords: Steganography, data hiding, fractal image compression, DCT. 1. Introduction One of the important application of data compression is image processing on digital images. It reduces the redundancy of image data to store it efficiently Multimedia data which is uncompressed (graphics ,audio , video ) need storage capacity & transmission bandwidth .Now a days there is rapid progress in mass storage density & digital communication system performance . The future of multimedia based web applications is data intensive , so we need to have efficient way to encode signal & images .Compression is achieved by the removal of one or more of three basic data redundancies: (1) Coding redundancy, which is present when less than optimal (i.e. the smallest length) code words are used(2) Interpixel redundancy, which results from correlations between the pixels of an image & (3) psycho visual redundancy which is due to data that is ignored by the human visual system (i.e. visually nonessential information).In this paper will mainly concentrate on the comparative study of compression techniques namely DCT (Discrete Cosine Transform) & Fractal Compression. 2. Review Of Compression Technique 2.1.DCT (Discrete Cosine Transform) : A discrete cosine transform (DCT) is a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. From lossy compression of audio and images to spectral methods for the numerical solution of partial differential equations , it turns out that cosine functions are much more efficient , whereas for differential equations the cosines express a particular choice of boundary conditions. Here is a block diagram explaining the same, followed by the decoding of the image. Fig 1 Encoding of DCT