LOW BITRATE HYBRID SECURED IMAGE COMPRESSION FOR WIRELESS IMAGE SENSOR NETWORK

SUSEELA G; ASNATH VICTY PHAMILA Y

doi:10.22159/ajpcr.2017.v10s1.19578

Authors

SUSEELA G School of Computing Science and Engineering, VIT University, Chennai Campus, India
ASNATH VICTY PHAMILA Y School of Computing Science and Engineering, VIT University, Chennai Campus, India

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.19578

Keywords:

Discrete wavelet transform, Binary discrete cosine transform, Nil, Encryption, Wireless image sensor networks

Abstract

Wireless image sensor networks are capable of sensing, processing and transmitting the visual data along with the scalar data and have attained
wide attention in sensitive applications such as visual surveillance, habitat monitoring, and ubiquitous computing. The sensor nodes in the network are resource constrained in nature. Since the image data are huge always high computational cost and energy budget are levied on the sensor nodes. The compression standards JPEG and JPEG 2000 are not feasible as they involve complex computations. To stretch out the life span of these nodes,
it is required to have low complex and low bitrate image compression techniques exclusively designed for this platform. The complicated scenario
of wireless sensor network in processing and transmitting image data has been addressed by a low complex hybrid secured image compression technique using discrete wavelet transform and Bin discrete cosine transformation.

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References

Karl H, Willig A. Protocols and Architectures for Wireless Sensor Networks. New York: John Wiley & Sons; 2007.

Suseela G, Phamila AV. Visual sensor networks: Critical infrastructure protection. In: Geetha S, Phamila YA, editors. Combating Security Breaches and Criminal Activity in the Digital Sphere. Hershey, PA: IGI Global Publications; 2016. p. 263-82.

Lee DU, Kim H, Rahimi M, Estrin D, Villasenor JD. Energy-efficient image compression for resource-constrained platforms. IEEE Trans Image Process 2009;18(9):2100-13.

Lecuire V, Makkaoui L, Moureaux JM. Fast zonal DCT for energy conservation in wireless image sensor networks. Electron Lett 2012;48(2):125-7.

Nasri M, Helali A, Sghaier H, Maaref H. Adaptive image compression technique for wireless sensor networks. Comput Electr Eng2011;37(5):798-810.

Duran-Faundez C, Lecuire V, Lepage F. Tiny block-size coding for energy-efficient image compression and communication in wireless camera sensor networks. Signal Process Image Commun 2011;26(8):466-81.

Kaddachi ML, Soudani A, Nouira I, Lecuire V, Torki K. Efficient Hardware Solution for Low Power and Adaptive Image-Compression in WSN. In: Electronics, Circuits, and Systems (ICECS), 2010 17th IEEE International Conference; 2010. p. 583-6.

Pham C, Lecuire V. Building Low-cost Wireless Image Sensor Networks: From Single Camera to Multi-camera System. In: Proceedings of the 9th International Conference on Distributed Smart

Cameras, ACM; 2015. p. 158-63.

Rein S, Reisslein M. Low-memory wavelet transforms for wireless sensor networks: A tutorial. IEEE Commun Surveys Tutor 2011;13(2):291-307.

Chen G, Mao Y, Chui CK. A symmetric image encryption scheme based on 3D chaotic cat maps. Chaos Solitons Fractals 2004;21(3):749-61.

Wu Y, Yang G, Jin H, Noonan JP. Image encryption using the two-dimensional logistic chaotic map. J Electron Imaging 2012;21(1):013014-1.

Meenakshi P, Manivannan D. An efficient three layer image security scheme using 3D Arnold cat map and Sudoku matrix. Indian J Sci Technol 2015;8(16):1-6.

Jolfaei A, Wu XW, Muthukkumarasamy V. On the security of permutation-only image encryption schemes. IEEE Trans Inf Forensics and Secur 2016;11(2):235-46.

Loukhaoukha K, Chouinard JY, Berdai A. A secure image encryption algorithm based on Rubikâ€™s cube principle. J Electr Comput Eng 2012;2012:7.

Gomathi T, Shivakumar BL. Multistage image encryption using Rubikâ€™s cube for secured image transmission. Int J Adv Res Comput Sci 2015;6(6):54-8.

Phamila AV, Amutha R. Energy-efficient low bit rate image compression in wavelet domain for wireless image sensor networks. Electron Lett 2015;51(11):824-6.

Tran TD. The bin DCT: Fast multiplierless approximation of the DCT. IEEE Signal Process Lett 2000;7(6):141-4.

Wallace GK. The JPEG still picture compression standard. IEEE Trans Consum Electron 1992;38(1):xviii-xxiv.

Golomb SW. Run-length encodings. IEEE Trans Inf Theory 1966;12(3):399-401.

Zhao D, Chan YK, Gao W. Low-complexity and low-memory entropy coder for image compression. IEEE Trans Circuits Syst Video Technol 2001;11(10):1140-5.

Kominek J. Waterloo Brag Zone. University of Waterloo; 1995. Available from: http://www.links.uwaterloo.ca/Repository.html. [Last accessed on 2015 Aug 07].

Ahmad J, Ahmed F. Efficiency analysis and security evaluation of image encryption schemes. Computing 2010;23:25.