Enhanced Efficient Halftoning Technique used in Embedded Extended Visual Cryptography Strategy for Effective Processing

Transcription

1 Enhanced Efficient Halftoning Technique used in Embedded Extended Visual Cryptography Strategy for Effective Processing M.Desiha Department of Computer Science and Engineering, Jansons Institute of Technology Coimbatore, Tamilnadu, India Vishnu Kumar Kaliappan Department of Computer Science and Engineering, Jansons Institute of Technology Coimbatore, Tamilnadu, India Abstract Visual cryptography is a fixed technique which allows visual information to be encrypted using an encoding system and decrypted by an automatic operation that doesn t need a terminal. A visual cryptography strategy (VCS) is a method of secret splitting strategy which converts a secret image into n portions of dual form.vcs is not highly-effective and highlyworth, because of the security issues. Due to various disadvantages of VCS, a popular method called extended visual cryptography strategy (EVCS) was developed, where the portion images are constructed to contain expressive cover images, thereby used for biometric security techniques. In this paper, we have proposed the effective dithering halftone technique for time reduction process on generating the halftone image and also for enlightening the visual quality of the secret image. The resulting strategy has good security and effective processing over the existing extended visual cryptography approach. Keywords- visual cryptography strategy (VCS), extended visual cryptography strategy (EVCS), dithering halftoning technique and secret splitting I. INTRODUCTION Visual cryptography is first presented by Naor and Shamir in 1994, is a secret splitting strategy, based on dual form [1]. The prime secret image is divided into n portions, which doesn t reveal any evidence of the prime secret. The n portions will be dispersed to n participants so that only by contraction all the portions will regenerate the secret image. kn, strategy generates n portions, but it More generally, a ( ) only compels k portions to contract to regenerate the secret image. Particularly, in a ( kn, ) threshold visual cryptography strategy (VCS), any suitable subset of participants should contain at least k participants, where k n. Visual cryptography has protection purpose based on biometrics [2]. The advantage over VCS is that it is simple and not complex and the disadvantages are size expansion of portions and low visual quality of the revealed image. This strategy does not have high quality and effect. The extended visual cryptography strategy (EVCS) which can construct expressive portion images to regenerate the prime secret was intended by Ateniese, Blundo and Stinson [3], where it gives a simple example of (2, 2) EVCS. The fixed VCS that have the same approach structure with the EVCS. In EVCS the portion images that are to be embedded contains expressive cover images. EVCS is similar to the technique of steganography. The purpose of EVCS is to avoid the custom reviews, because the portions of EVCS are communicative images, hence this makes very few chances of suspecting and detecting the portions. In [4] the embedded extended visual cryptography strategy (EEVCS) gives the overall good properties. By comparing the intended strategy with the existing strategies of well-known EVCS, the intended strategy has competitive visual quality. Besides, the EEVCS strategy has more specific advantages over these well-known EVCSs. In order to improve the modest visual quality of the image in [3, 4] an innovative technique named halftone visual cryptography was intended. The halftone process was intended to achieve the visual cryptography via halftoning. The halftone techniques used in [3, 4] gives a progress quality from the existing techniques. In [4] the dithering halftoning technique is used which gives good quality but the drawback is that when the dimension of the dithering matrix is less the halftone processing is slow. The intension of the research outlined in this paper is by enlarging the dimension of the halftone dithering matrix. By doing so the halftoning process timing is reduced. The rest of the paper is organized as follows. Some related works are reviewed in section II. II. RELATED WORK In this section, we give some explanation about VCS and EVCS and their use in our paper /15/$ IEEE

2 A. VCS kn VCS is to portion a dual secret image into n portions in [1]. The secret image can be revealed by combining any k portions. A ( kn, ) VCS consist of two collections of a b matrices C and C 1. To portion a white secret pixel chooses the portion matrix C and to portion a black secret pixel chooses the portion C. Then distribute each row of the chosen matrix to The concept of (, ) matrix 1 the corresponding portion as the block of sub-pixels. Example 1: Two basis matrices of (2, 2) VCS are constructed by Naor and Shamir s strategy as follows: advantage of EEVCS is that, it is very secure in hiding the secret portions into the cover images that cannot be easily retrieved by an unauthorized member. In [3] the (2, 2) EVCS there is pixel expansion in the recovered image, this drawback is avoided in [5], Figure. 2 shows the input images for (2, 2) EVCS (a) Cover image 1(b) Cover image 2 (c) Secret image. (a) (b) B 1 = 1 B 1 1= 1 The two portion matrices C and C 1 are constructed from the basis matrices B and B 1 by permuting the columns of B and B 1, respectively. Figure. 1 (a) Secret image; (b) Portion 1; (c) Portion 2; (d) Revealed secret image. (c) Figure 2: An example of (2, 2) EVCS input images (a) Cover image 1 (b) Cover image 2 (c) Secret image (cited in [5]) (d) (a) (e) (b) (c) (d) Figure 1: An example of (2,2) VCS (a) Secret image (b) Portion 1 (c) Portion 2 (d) Recovered secret image (cited in [1]) B. EVCS An Extended Visual Cryptography Strategy (EVCS) is a kind of VCS which consist of expressive images, when compared to the random portions of fixed VCS. EVCS is also treated as a technique of steganography. A construction of EVCS is realized by embedding the secret portions into expressive cover images and we call it as embedded EVCS. When comparing the result of EEVCS result in [4] to some of the well-known EVCSs intended in recent years has a competitive visual quality in the literature. The specific (f) Figure. 3: Shows the Embedded cover images and Recovered secret image of (2, 2) EVCS (d) Embedded Portion 1 image (e) Embedded Portion 2 image (f) Recovered secret image (cited in [5]) The Figure. 3 shows the embedded cover images and recovered secret image (d) Embedded Portion 1 image (e) Embedded Portion 2 image (f) Recovered secret image. The recovered secret image is got by combining (d) and (e) image will regenerate the prime secret image (f). III. SYSTEM ARCHITECTURE The overall system flow chart is shown in Figure. 4 that shows the detailed flow of the whole working of the system intended in step by step. Each processing is explained in detail in the subdivision of A, B and C, respectively. Step 1: Input images like Cover image 1, Cover image 2 and Secret image. Step 2: Convert the secret image to gray secret image. Step 3: Use the converted image for halftone process to get the halftone secret image.

3 Step 4: The output halftone secret image is used as an input for portion generation. Here, secret portion 1 and portion 2 images are generated. Step 5: The generated portion 1 and portion 2 are embedded into the cover images. The portion 1 is embedded into the cover image 1 and portion 2 into the cover image 2. Step 6: The embedded portion images are fed into the extraction process, where the extraction of portion images from cover images are done. And the extracted portions are combined together to recover the prime secret image. {,..., cd} as the gray-level of a pixel in the prime, the g image. Normally, for an input image I of size p halftoned process will move over each pixel in I. The intended halftoning process moves on each pixel in I as explained in Algorithm Figure. 5: Shows the patterns of dithering matrix D of ten gray-level,..., 9 (cited in [4]) q Figure. 4: Shows the system flow chart A. Pre-processing In this first phase, we have loaded the input images for halftoning process. The secret image is converted into gray image and the converted image is used for halftone process. In the intended work the pattering dithering halftone technique is used for generating the halftone image. This dithering halftone technique is used to produce halftoned pattern at the position of the pixel x. The dithering matrix c d is denoted as D.The entries, denoted as Dij for i c 1 and i d 1, of the dithering matrix between and cd 1.Note that Algorithm 1: The halftoning process for each pixel x in image I : Input: c d dithering matrix D and a pixel x with g as gray-level in input image I Output: The halftoned pattern at each location of the pixel x For i = to c 1 do For j = to d 1do If g D then print a black pixel at the location (i, j); ij Else print a white pixel at location (i, j); Example 2: Dithering matrix D is shown below. k n Dithering matrix D with ten gray-levels D = The above dithering matrix D is taken as example, the patterns of gray-levels,...,9 are shown in Figure. 5.If the gray-levels of all the pixels in the image I are smaller than 4, then the locations corresponding to D, D1, D2, D 11 and D12 are always black even after halftoning, where Dij indicates the ith row and jth column of D. The drawback in [4] is that, as the gray-level decreases the halftoned image produced will become darker. The outcome of the image won t be in good quality. In order to avoid this drawback the patterning halftone is removed and a new enhancement is done here for progress quality as well as for time reduction in halftone process. The enhanced algorithm for dithering halftoning technique is shown in the Algorithm 2.

4 B. Embedding the generated portions Embedding is the second phase; the secret image generates two or more portions, where EVCS is used for embedding each portion into the expressive cover images. The n portions are given as input, with the corresponding VCS ( C, C ) with pixel expansion m and secret image I. The 1 output produced will be having n embedded portions e, e1,..., en 1. For doing this, divide the portions t m subpixels each. Choose into blocks that contain ( ) m embedding positions in each block in the n covering portions. For each black pixel in I, randomly choose a portion matrix M C1 and for each white pixel in I, randomly choose a portion matrix M C. Embed the m sub pixels of each row of the portion matrix M into the m embedding positions. Hence the pixels in the embedding positions are replaced by the sub pixels of the portion matrix. Figure.6 showed below shows how the portions are embedded into the cover images... Portion 1 Portion 2 n Portions IV. ENHANCED EFFECTIVE DITHERING HALFTONING PROCESS The intended pattering dithering halftone algorithm in [4] is enhanced for its effective processing of time reduction and progress quality of image, as the intended algorithm in [4] is a time consuming process having no progress quality of the image. Algorithm 2: Enhanced Effective Dithering Halftoning Process Input: The dimension of the dithering matrix num is inputted. Output: The elapsed time for various dimensions is measured and a good visual quality halftoned image is generated Step 1: Enter the dimension value num for the dithering matrix as 2, 4, 8 or 16. Step 2: if num ==2 then B = B ; num (, i j ) Else if num ==4 then B = num Else if num ==8 then B = num Else if num ==16 then B = B ; B ; B num ; Else entered a wrong dimension value for the dithering matrix; 1 3 Step 3: Base matrix B = num (, i j ) 2 4 is calculated with the e e 1 en = Cover1 Cover 2 n covers Stacking 4 B + B 4 B + B B num = 2 4 B + B 4 B + B different dimension value num. ( num 2)/4 num (,) ( num 2)/4 num (,1) ( num 2)/4 num(1,) ( num 2)/4 num (1,1) Step 4: For i = to c 1 do for Portion 1 Portion 2... Figure.6: Shows the embedding of the generated portions C. Extracting the portions Extraction is the third phase, in order to extract the secret image the only process can be done by stacking the portions that were embedded. At this point, by stacking the embedded portions of the secret image is revealed, the t m subpixels that have not been embedded by the secret subpixels are black and the m subpixels that are embedded by the secret subpixels recover the secret image as the corresponding VCS does. Hence the secret image is recovered through extraction process. For j = to d 1 do If g D then print black pixel at position (i, j); ij Else print white pixel at position (i, j); V. EXPERIMENTAL RESULT The experimental results are shown in Figure. 7 shows the result of the loaded secret image and the converted gray secret image. The Figure. 8 shows the result of the halftoned image using dithering technique. The table I. gives the measurement of the time taken by the halftoning process, where the time reduction happens for various dimension of the dithering matrix. The 2 2 dimension of the dithering matrix

5 has the highest elapsing time as seconds. The 4 4dimension of the dithering matrix has the elapsing time seconds as less when compared to 2 2 dimension. The 8 8dimension of the dithering matrix has the elapsed time seconds as less when compared to 4 4 and 2 2 dimensions. The dimension of the dithering matrix has the elapsed time seconds as less when compared to8 8, 4 4 and 2 2 dimensions. And the Figure. 9 shows the example result for 2 2 dimensions elapsed timing for halftoned image using dithering matrix in the command window. Table I: Measurement of timing for various dimensions Number of Results Dimension of the dithering matrix Elapsed time 1. 2x seconds 2. 4x seconds 3. 8x seconds 4. 16x seconds VI. CONCLUSION In this paper, we have intended EVCS for embedding the random portions into the expressive covering portions. And also we have shown that using the pre-processing of halftone images, we are able to produce halftone image in good quality and also time reduction being done for halftoning process. The halftoning technique used in EVCS gives more advantages over conventional methods. Figure. 7: Experimental Result for input secret image and converted gray secret image Figure. 8: Experimental Result for Halftoned image using Dithering technique REFERENCES [1] M. Naor and A. Shamir, Visual cryptography, in EUROCRYPT 94 Proceedings, Lecture Notes in Computer Science, Springer-Verlag, vol. 95, pp. 1-12, [2] A. Ross and A. A. Othman, Visual Cryptography for Biometric Privacy, IEEE Transactions on Information Forensics and Security, vol. 6, no. 1, pp. 7-81, 211 [3] G.Ateniese, C.Blundo, A.De Santis and D.R.Stinson, Extended Capabilities for Visual Cryptography, Theoretical Computer Science, vol. 25, pp , 21. [4] Feng Liu and Chuankun Wu, Senior Members, IEEE, Embedded Extended Visual Cryptography Schemes, IEEE transactions on information forensics and security, vol.6, no. 2, June 211. [5] N.Askari, H.M.Heys, and C.R.Moloney, An Extended Visual Cryptography Scheme without pixel expansion for halftone images, 26th annual IEEE Canadian conference on electrical and computer engineering year 213. [6] Zhi Zhou, Member, IEEE, Gonzalo R. Arce, Fellow, IEEE, and Giovanni Di Crescenzo, Halftoning visual Cryptography, IEEE transaction on image processing, vol. 15, no. 8, august Figure. 9: Example result for 2 2 dimensions elapsed timing for halftoned image using dithering matrix.