Proceedings of2013 IEEE Conference on Information and Communication Technologies (ICT 2013) CONVERSION OF 2D STEGANO IMAGE·S INTO A 3D STEREO IMAGE USING RANSAC. M. Shrikalaa, P .Mathivanan , J.S.Leena Jasmine Department of Electronics and Communication Velammal Engineering College, Chennai, India shrikalaa_mohan(£qyahoo.co.in, mathiecetrS cti],glnail. com, lena~ victor(@yahoo.co.in. ABSTRACT- In this paper we proposed a steganogra phy with maxlmu In data hiding capacity. In order to increase data hiding, 2D Anaglyphic stereography images arc used for this process. The 2D A.naglyphic stereo input images of different colours and coloured filters in front of each eye allows only the appropriatc image to pass. SonIC international standards body has decided that the right eye filter should be blue, while the left eye filter is red, but this can vary. In our process these input images arc individually processed, further these input images arc individually stegano with a secret data (image). The data hiding process is obtained by a simple method of stegano algorfthm called LSD (Least Significant bit), here LSB bit of our cover image is replaced by a secret data. Later this individual stereo images with secret data is applied to Stabilization Using Point Feature Matching, this stabilization algorithm involves h\,TO steps. First, we determine the affine image transformations between all neighbouring frames of a video sequence using a Random Sampling and Consensus (RANSAC) [1] procedure applied to point correspondences between images. Second, we warp the embedded 2D Anaglyphic steganned images to achieve a stabilized 3D stereo image with high data hiding capability, which contains two secret data in a single 3D stereo Image. ""0 Keywords: 2DA.naglyphic stereo images, LSB, Random Sampling and Consensus (RANSA'C) INTRODUCTION NO\\l a days, information security is very important. Cryptography was created as a technique for securing the secrecy of cornmunication and many different methods have been developed to encrypt and decrypt the data in order to keep the message secret. Unfortunately it is sometimes not enough to keep the contents of a message secret, it may also be 978-1-4673-5758-6/13/$31.00 © 2013 IEEE necessary to keep the existence of the message secret, The existing system was carried out with heuristic, LZ\V, AES and DES algorithm. But in these algorithms the data hiding efficiency is very less. In order to overcome these drawbacks we go for steganography process. In the steganography the information is hidden exclusively in images, Today steganography is mostly used on computer with digital data being the carriers and network. Steganography differs from cryptography in the sense that where cryptography focuses on keeping the contents of a message secret, steganography focuses on keeping the existence of a message secret[7 ~ 15J. The main 0 bj ective of this technique is to communicate securely in such a way that true message is not visible to the observer. Steganography can be used for wide range of applications such as defence, in military, in confidential communication and in intelligence agencies. Also in medical imaging for maintaining the medical report of a person secretly and in mobile banking etc. Capacity, robustness and invisibility are important parameters in information hiding. This paper proposes a novel steganography for digital colour image which achieves high data by using 3D stereography technique. PROPOSED METHOD The main aim of our project is to improve the data hiding capability with the help of stereography technique. In this process we individually split the stereo input images, one with respect to right and another one with respect to left of the stereo input obtained from the stereo image capture setup. The cover image and secret image used for this process can be of any format such as lPEG ~ BrvIP and TIF etc. The secret image is to be embedded into the input cover image by using LSB algorithm technique. [1,3 J. 686 Proceedings of2013 IEEE Conference on Information and Communication Technologies (ICT 2013) Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image. The least significant bit (in other words, the 8 th bit) of some or all of the bytes inside an image is changed to a bit of the secret message. Once the data hiding of secret imaging is done further the individual stegano images is converted into a 3D stereo image were stegano outputs are merged using a 3D stereography image which improves the data hiding capability of steganography and this 3D stereography output image has less attraction. The mam stages employed in our process are Preprocessing, (LSB) E111 bedding algorithm and Stabilization Using Point Feature lVlatching (Stereography). These three stages of converting 2D cover images to a 3D stereo image with high data hiding capability are discussed the following section. [ 1-6J Figure 2 2D stereo input one with respect to right eye and another wi th respect to left eye (a) and (b) PREPROCESSING The main purpose of this step is to enhance the image and remove the unwanted noise signals present in the image. This step also includes noise removal and image resizing. The input stereo image may contain some unwanted noise signals. The most frequently occurring noise is salt and pepper noise which is caused due to lens vibration. This noise is removed by passing it through the median filter. This type of filter is widely used in this technique because under certain conditions it preserves edges. STEGANOGRAPHY USING LSB (LEAST SIGNIFICANT BIT) As stated earlier, images are the most popular cover objects used for steganography, In the domain of digital images many different image file formats exist, most of them for specific applications. For these different image file formats, different steganographic algorithms exist. But in our process of data hiding we use LSB algorithm for data hiding. Figure 1 Block diagram of our Proposed system 978-1-4673-5758-6/13/$31.00 © 2013 IEEE Figure 3 LSB embedding techniques 687 Proceedings of2013 IEEE Conference on Information and Communication Technologies (ICT 2013) Ahnost all digital file formats can be used for steganography, but the formats that are more suitable are those \~ ...ith a high degree of redundancy. Redundancy can be defined as the bits of an object that provide accuracy far greater than necessary for the object's use and display. The redundant bits of an object are those bits that can be altered without the alteration being detected easily. The least significant bit insertion method is probably the most well known image steganography technique. It is a common, simple approach to embed information in a graphical image file. Unfortunately, it is extremely vulnerable to attacks. By means of the least significant bit i.e, the eighth bit inside an image is changed to a bit of the secret message. When using a 24-bit image, one can store 3 bits in each pixel by changing a bit of each of the red, green and blue colour components, since they are each represented by a byte. [7-15] Steps to En1beddedNIessage into Cover Itnage Using LSB Step 1- initialise number of bit to be embedded (n), Step2 - message image is bit shifted the LSB bits as per the initialisation (n) here each bit of the message is shifted right (example - A=1001(9 in decimal), n=2 bit shift output of will be A=100100 (36 in decimal». Step3 - in c·over image LSB bits are bit set as per the initialisation mentioned in the embedding process here LSB bits of the cover image is set to zero( example B=1001(9 in decimal),n=2 is applied for bit set operation B= 1000(8 in decitnal) ) Step 4 - from the bit shifted message and bit set cover image is further app lied for embedded operation to obtain steganoed images (stegano= (message + cover». figure 4 secret data to be embedded after bit shifted The above embedding process is applied for the both input of the 2D Anaglyphic images and its embedding process is verified to checkwhether our cover itnage quality is good after the stegano process is verified using the expression of wiSE and PSNR and its results are tabulated. After the analysis these 2D stegano images are applied for stereo. 1 l'vl SE == 11/-1 1/-1 -L L In [1 (i, j) - K (i, j)J2 11 j=O /=0 Table 1 shows PSNR after embedded process to show data hiding capacity Input Image 1 Stegano Image 1 Input Image Size in (KB) 9.65 Dimension 9.65 250.:<.230 6.41 292x214 250x230 2 Stegano Image 2 6.41 292);;214 PSNRafter embedding process (dB) PSNR R=39.546 PSNR - G=39.466 PSNR B=39.512 PSNR R=43.144 PSNR --G=43.102 PSNR B=43.144 STABILIZATION USING POINT FEATURE NiATCHING This process of stabilization using point feature matching is used to convert t\VO 20 images to a single 3D stereo image which involves t\VO main steps for this conversion. First,\ve determine the affine image transformations between all neighbouring frames of a video sequence using a Random Sampling and Consensus (RANSAC) [1] procedure applied to point correspondences between t\VO images, Second, we \varp the embedded 2D Anaglyphic steganoed images to achieve a stabilized 3D stereo image with high data hiding capability and these t\VO steps are obtaining 3D image is explained as follows. RAl\rdom SAmpling and Consensus (RAl\rSAC) It is a mathematical model that uses an interactive method to estimate the parameters from a set of observed data. It is a resampling process with a nondeterministic algorithm, which means it produces a reasonable result only with a certain probability. In RANSAC algorithm we repeatedly use two process they are hypothesize and test. [16-17] Figure 5 (a) and (b) stegano output 978-1-4673-5758-6/13/$31.00 © 2013 IEEE Hypothesize uses minimal sample sets (lV1SS) that randomly selects the input data and parameter that are computed using input from lV1SS. 688 Proceedings of2013 IEEE Conference on Information and Communication Technologies (ICT 2013) n=the number of random points to pick every iteration in order to create the transform. k= the number of iterations to run. t= the threshold for the square distance for a point to be considered as a match. d = the number of points that need to be matched for the transformation to be valid image point! and image point 2. In our hypothesize process we initially selects the random samples based on the value of n, t and d which are initialised at the first stage using 1\1SS parameters for both steganoed image. CONCLUSION This paper describes about the steganographic technique for hiding an image by using least significant bit algorithm and to improve its data hiding efficiency using stereography techniques. With this proposed technique the data hiding efficiency is increased by twice than the previous techniques which are shown in the table. The two input images of size 9.65 KB one wi th respect to right eye another one with respect to left eye are individually steganoed with a different secret data of various size. This stegano image of size 6.41 KB are further converted into a single stereo image of size 11.4KB using RANSAC with t\VO hidden secret data in a single 3D image. '\l e have also tested our image using PSNR, NISE and histogram equalisation techniques. 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