 Digital images store large amounts of data and information. This data can be manipulated to some extend without being detected by human eyes.  DWT(Discrete Wavelet Transform) are applied this technique

 Watermarking protocol used for only send the image in embedding to the content owner image  Seller dose not exact watermarked copy that the buyer services  visible watermarking techniques  Public key cryptography and private key are used

 Communicate only image seller, buyer and also the third parity can see that the image  No security  Restrict our invisible process

 Lossless data embedding techniques  Two techniques are used i) Payload extractions is robust ii) Feature of the images  Spatial domain algorithm are used  There are comprises of three components i) Prediction ii) context modeling and quantization iii) conditional entropy coding

 The process is irreversible  It offers the distortion curve and capacity  Compression efficiency is low

 An analysis of the local standard deviation of the marked encrypted image in order to remove the embedded data during the decryption step.  AES algorithm  This algorithm has several modes are used but now used for ECB(Electronic Code Book)  Symmetric key are used

 Only applied for the medical images  Payload and complexity is low  Efficiency is low

 Watermaking techniques may be applied in the without fear of image destruction due to lossy compression because they are more integrated into the image  Algorithm used for DCT (Discrete Cosine Transform) which is used in JPEG compression  It is a spatial domain  DCT depend on time or frequency domain

 watermarking schemas is that they are not very robust against different types of image manipulations or attacks.  Zigzag error is produced  some of these techniques are quite complicated to implement in real-time.

 DWT(Discrete Wavelet Transform)  The discrete wavelet transform (DWT) is being increasingly used for image coding.  This is due to the fact that DWT supports features like progressive image transmission (by quality, by resolution), ease of compressed image manipulation, region of interest coding, etc.  DWT has traditionally been implemented by convolution.

‣No need to divide the input coding into non-overlapping ‣Transformation of the whole image ‣It depend on time and frequency domain ‣Compression ratio is high ‣Higher flexibility Performance ‣ Peak Signal to Noise ratio used to be a measure of image quality ‣ The PSNR between two images having 8 bits per pixel or sample in terms of decibels (dBs) is given by: ‣ PSNR = 10 log ²/MSE

key secret data key DWT EmbeddingOPA Stegno image Inverse transform Extraction message input image IMAGE ENCRYPTION DATA EMBEDDING DATA EXTRACTION

 There are three methods i) Image encryption ii) Data embedding iii) Data extraction/Image recovery

 By embedding data in only certain region  Image cropping concept introduced, maintains security at respectable level since no one can extract message without having value of cropped region.  It increases the quality of stego image.  The proposed approach provides fine image quality.

 Secret communication  Defence application  Medical image application

 Software tool Tool : Matlab Version : 7 Operating system : windows7

 A novel lossless (reversible) data embedding technique – Lossless G-LSB  Embedding capacity is high  Low distortion

 N.Menon and P.W.Wong,‶A buyer seller watermarking protocol″,IEEE transactions. image process.,vol 10.no 4,april 2001  Z.Ni,Y.Q.Shi,N.Ansari,and W.Su, ‶ Reversible data hiding ″,IEEE transactions. image process.,vol 16.no 3,March 2006  X.Zhang, ‶ Reversible data hiding in encrypted images″IEEE signal process.,vol 18.pp ,April 2011

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