1. Title of On the Implementation of a Information Hiding Design based on Saliency Map A.Basu, T. S. Das and S. K. Sarkar/ Jadavpur University/ Kolkata/ India/ idabhishek23@yahoo.com, tirthasankardas@yahoo.com, su_sircir@yahoo.co.in Swanirbhar Majumder/NERIST (Deemed University)/ Itanagar/ India/ smd@nerist.ac.in In this paper, an adaptive spatial domain image watermarking scheme is proposed which embeds watermark information to the uneven bit depth salient image pixels. Watermarked image thus produced has better visual transparency with respect to human visual system (HVS) with high payload capacity. In proposed scheme, salient pixels are determined using the bottom- up Graph-Based Visual Saliency (GBVS) model. Experimental results reveal that proposed scheme has less perceptual error as well as improved robustness than existing spatial domain embedding scheme. The visual attention model consists of two steps: first forming activation maps on certain feature channels, and then normalizing them in a way which highlights conspicuity and admits combination with other maps. The model is simple and biologically plausible insofar as it is naturally parallelized The Performance Results with Comparisons:In this paper, a new spatial domain adaptive image watermarking scheme is proposed which embeds watermark information in the least significant bit depth pixels with respect to a well known selective visual attention model GBVS. It is experimentally shown for a significant percentage of images the saliency distribution of pixels remain same even after embedding in multiple bit plane LSB embedding. Experimental result also reveals that the perceptual transparency error due to embedding in proposed scheme is less than that of normal LSB embedding scheme. In the attacked environment, this blind proposed scheme can be easily used to make the method visually more robust. INTRODUCTION RESULT CONCLUSIONS REFERENCES Nov 3-5 2011 1.Kutter, M., et. Al. “Image watermarking techniques, Proceedings ofthe IEEE, Special Issue on Identification and Protection of Multimedia Information, 1999. 2.Itti, L., Koch C., Niebur E.: A model of saliency based visual attention for rapid scene analysis, IEEE Trans. on PAMI, vol. 20, pp. 1254-1259,1998. 3.O.LeMeur, D.Thoreau, P.LeCallet and D.Barba, A Spatio Temporal Model of the Selective Human Visual Attention, 4.Mickael Guironnet, Nathalie Guyader, Denis Pellerin and Patricia Ladret, Static and Dynamic Feature based Visual Attention Model: Comparison to Human Judgment. 5.Christopher Wing Hong Ngau, Li-Minn Ang and Kah Phooi Seng, Bottom-up Visual Saliency Map Using Wavelet Transform Domain, 978-1-4244-5540-9/10 ©2010 IEEE. 6.Arijit Sur, et. al, “A New Image Watermarking Scheme using Saliency Based Visual Attention Model”, IEEE 978-1-4244-4859- 3/09/©2009 7.C.C. Chang, et. al, Finding optimal least-significant-bit substitution in image hiding by dynamic programming strategy, Pattern Recognition 36 (2003) 1583–1595 8.C.C. Chang,, et. al, A block based digital watermarks for copy protection of images, Proceedings of Fifth Asia-Pacific Conference on Communications/Fourth Optoelectronics and Communications Conference, Beijing, China, Vol. 2, 1999, pp. 977–980. 9.Cheng-HsingYang, Inverted pattern approach to improve image quality of information hiding by LSB substitution, Pattern Recognition 41 (2008) 2674 – 2683. 10.Chang-Lung Tsai,, et. al, Reversible data hiding and lossless reconstruction of binary images using pair-wise logical computation mechanism, Pattern Recognition 38 (2005) 1993 – 2006. WATERMARK ENCODER & DECODER Sl. No. MethodTPEPSNR Capacity (bpp) Salient Watermarking Model 1Sur et. al [6]14.88x10 -5 N.A0.0017 2Our Method0.048542.62874 Non Salient Watermarking Model 1 LSB substitution [7] N.A38.34253 2GA[8]N.A38.32203 3IP LSB [9]N.A35.07514 4Optimal LSB [9]N.A34.90654 5PWLC [10]N.A48.35000.68 Sl.ParameterResult 1SNR32.4235 dB 2MSE10.0539 3PSNR42.6287 dB 4IF0.99943 5MD 7 6AD2.3418 7AVD0.043198 8NAD0.018951 9NMSE0.00057234 10LMSE0.051607 11SER11.058 12KLD0.80179 13UIQI0.9979 14SSIM0.9557 15MSSIM0.9904 16VSNR32.2061 17VIF0.8235 18PVIF0.7821 19IFC7.6012 20NQM26.1997 21WSNR37.0613 22SC0.999986 23PQS3.662338 24TPE0.0485 Performance analysis results for imperceptibility:  CONTACT: Name: S. Majumder EMAIL: smd@nerist.ac.in