Digital image watermark key extraction with Encryption and Decryption Scheme in matlab
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Fig. 8 Image with embedded watermark
Fig. 9 Extracted watermark The proposed method is also used to decompose the blocks including multi-line texts into single line text. According to the experimental results, the proposed method is proved to be efficient for extracting the watermark text regions from the image. In the fig. 6, Original image is of vehicle plate which has the number MX55NOB. The encrypted watermark is shown in fig. 7, which is copyright@author India Do’t. Copy.After encryption watermark fig. 8 is approximately same because watermark is embedded with the image and under invisible watermarking technique. After MATLAB simulation and watermark extraction/ decryption , the same watermark key is extracted copyright@author India Do’t. Copy, as shown in fig.9. Conclusion The watermark key text extraction on the colour images using mathematical morphology and Haar DWT is done successfully with the concept of encryption and decryption. Applications of text extraction are huge including the making of digital copies of the ancient scripture to everyday life bills etc. It may be required to be of digital form. Digital watermarks provide an efficient cost effective means of a digital image which may be used for copyright protection. In watermarking technology, the watermark key is unique and exhibits a one-to-one correspondence with every watermark. The key is private and known to only authorized parties, eliminating the possibility of illegal usage of digital content. The watermarking scheme is simulated successfully in MATLAB. The work is carried out for images. In the future work, further research can explore with the techniques to recognize the special characters from colour images. The limitation of the watermarking algorithms implemented is that the processing needs to be done pixel-by-pixel. In future development, we are aiming to investigate block-by-block processing. Digital watermarking find applications in the defense sector where it is must to transmit data secretly. REFERENCES [1] A. Tognetti, F. Lorussi, R. Bartalesi, S. Quaglini, M. Tesconi, G. Zupone, and D. De Rossi, “Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation,” J. Neuroeng. Rehabil., vol. 2, no. 1, p. 8, Mar. 2005. [2] A. M. Eskicioglu and E. J. Delp, “An Overview of Multimedia Content Protection in Consumer Electronics Devices,” Elsevier Signal Processing: Image Communication, vol. 16, pp. 681–699, 2001. [3] ArnabSinha and SumanaGupta,“A Fast Nonparametric Non causal MRF-Based Texture Synthesis Scheme Using a Novel FKDE Algorithm” IEEE Transactions on Image Processing, No.3, March 2010. [4] D. Dhanasekaran and K. BoopathyBagan (2004) “HIGH SPEED PIPELINED ARCHITECTURE FOR ADAPTIVE MEDIAN FILTER,” European Journal of Scientific Research ISSN 1450-216X Vol.29 No.4, pp. 454-460. [5] JulindaGllavata, Ralph Ewerth and Bernd Freisleben, A Robust algorithm for Text detection in images, Proceedings of the 3rd international symposium on Image and Signal Processing and Analysis, 2003. [6] J.D. Foley, A. van Dam, S.K. Feiner and J.F. Hughes, Computer Graphics, Principles and Practice, Addison-Wesley, Reading, 1990 [7] M. Hussain and M. Hussain, “Information Hiding Using Edge Boundaries of Objects”, International Journal of Security and its Applications, http://www.sersc.org/journals/IJSIA/vol5_ no3_ 2011/1.pdf, vol. 5, no. 3, (2011), pp. 1-10. [8] Mohammad Nuruzzaman, “Digital Image Fundamentals in MATlAB,”Author House 08/23/05, ISBN 1-4208-6965-5 (sc), 2005. [9] M. S. Hsieh, D. C. Tseng, and Y. H. Huang, Hiding Digital Watermarks using Multiresolution Wavelet Transform, IEEE Trans. on Industrial Electronics 48 (2006), no. 5, 875–882. [10] Sunil Kumar, Rajat Gupta, NitinKhanna, Student Member, IEEE, SantanuChaudhury, and Shiv Dutt Joshi (2007) “Text Extraction and Document Image [23] Segmentation Using Matched Wavelets and MRF Model” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 16, NO. 8, pp 2117-2129. [11] T. Barbu, 2011, “An Automatic Face Detection System for RGB images”, in Int. J. of Computers, Communications & Control ISSN, 1841-9836, E-ISSN, 1841-9844, Vol No.1, pp.21-32 [12] Victor Wu, RaghavanManmatha, and Edward M.Riseman, Text Finder: An Automatic System to Detect and Recognize Text in Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 11, November 1999. 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