127

REFERENCES

[1] S. Ramesh, B. Ramamoorthy,” Measurement of surface finish using an

optical diffraction technique” Manufacturing Engineering Section,

Department of Mechanical Engineering, Indian Institute of Technology,

Madras 600036, India Received 30 May 1995; accepted 5 October 1995.

[2] Irem Y. Tumer, R.S.Srinivasan, Kristin L. Wood, “Characteristic

Measures for the Representation of Manufactured Surface Quality ”,

ASME design Engineering Technical Conference and Design for

Manufacturing Conference, Irvine, California, August (18-22) 1996.

[3] S.Livens, P.Scheunders, G.Van de Wouwer, D.Van Dyck,“Wavelets for

Texture Analysis”, University of Antwerp, Belgium, 30th June 1997.

[4] M.Malfait and D.Roose, “Wavelet based image denoising using a Markov

Random Field a priori model”, IEEE Transactions on Image Processing,

vol. 6,no. 4, pp. 549–565, 1997.

[5] Paul Layzell, “Reducing Hardware Evolution’s Dependency on

FPGAs”, proceedings of the Seventh International Conference on

Microelectronics for Neural, Fuzzy and Bio-Inspired Systems(Micro

Neuro'99),IEEE 1999,pp.171-178, 1999.

[6] J.D.Lohn and S. P. Colombano, “A circuit representation technique for

automated circuit design”, IEEE Transactions on Evolutionary

Computation, 3(3):205.219, September 1999.

[7] Qinghu Chen, Shunian Yang, Zhu Li, “Surface roughness evaluation by

using wavelets analysis”, Research Centre of Measurement Technology

and Scientific Instruments, Huazhong University of Science and

Technology, Wuhan, Hubei, 430074, China, 22 March 1999.

128

[8] Bruno Josso , David R. Burton, Michael J. Lalor,“Wavelet strategy for

surface roughness analysis and characterization ”, Coherent and Electro-

optics Research Group (CEORG),School of Engineering, Liverpool John

Moores University, Byrom Street, Liverpool, UK L3 3AF, November

2000.

[9] Diaz-Sanchez and J. Ramirez-Angulo, “An Analog Median Filter for

Very Low Power Applications”, Proceedings of the 43th IEEE Midwest

Symposium on Circuit and Systems, East Lansing, Michigan. October

8-11, 2000.

[10] J.Candesand and D.L.Donoho, “Curvelets, multi-resolution representation

and scaling laws”, Wavelet Applications in Signal and Image Processing

VIII, A.Aldroubi, A.F.Laine, M.A.Unsereds., Proceeding, SPIE 4119,

2000.

[11] Fan Yang, Michel Paindavoine, “A New Image Filtering Technique

combining a wavelet transform with a Linear Neural Networks:

Application to Face Recognition”, Universit’ e de Bourgone, France, The

University of Texas at Dallas program in Cognition, U.S.A., 2000.

[12] R.Saatchi, P. Taylor, J.R. Travis, M. Wybrow, “Fuzzy Logic Cluster

Analysis of Surface Roughness Waveforms Generated Using a Laser-

Based System”, Sheffield Hallam University, UK, 2001.

[13] S.Jean-Luc, E.J.Candes and D. L.Donoho, “The Curvelet transform for

image denoising”, Image Processing, IEEE Transactions , vol. 11, pp.

670-684, 2002.

[14] L.Sekania,“Image Filter Design with Evolvable Hardware”, Applications

of Evolutionary Computing Proceedings of the 4th Workshop on

Evolutionary Computation in Image Analysis and signal Processing

(EvoIASP 02), Springer – Verlag, Berlin,pp.225-266, 2002.

129

[15] Bruno Josso, David R. Burton, Michael J. Lalor, “Frequency normalised

wavelet transform for surface roughness analysis and characterisation”,

Liverpool John Moores University, Liverpool, UK, 10th January 2002.

[16] M. N. Do and M. Vetterli, “Contourlets,” in Beyond Wavelets, Academic

Press, New York, 2003.

[17] D. Y. Po and M. N. Do, “Directional multiscale modeling of images using

the contourlet transform”, submitted to IEEE Trans. On Image

Processing, 2003.

[18] R.Eslami and H.Radha, “On Low Bit-Rate Coding Using the Contourlet

Transform”, Conference Record of the Thirty-Seventh Asilomar

Conference on Signals, Systems and Computers, vol.2,pp.1524-1528,

2003.

[19] Sekanina.L, “Virtual Reconfigurable Circuits for Real-World

Applications of Evolvable Hardware”, in proceeding of the 5th

International Conference Evolvable Systems: From Biology to Hardware,

ICES 2003, Trondheim, Norway, LNCS 2606, Springer-Verlag, p. 186-

197, 2003.

[20] B.A.Draper, “Accelerated image processing on FPGAs”, IEEE

Transactions on Image Processing, 12(12):1543 - 1551, Dec. 2003.

[21] R. Eslami and H. Radha, “The Contourlet transform for Image Denoising

Using Cycle Spinning”, Conference Record of the thirty-Seventh

Asilomar Conference on Signals, Systems and Computers, vol.2, pp.1982-

1986, 2003.

[22] J. Yang and D. Zhang, “Two-dimensional PCA: A new approach to

appearance-based face representation and recognition,” Pattern Analysis

and Machine Intelligence, IEEE Transactions, vol. 26, pp. 131-137, 2004.

130

[23] Abdullah Al Muhit, Md. Shabiul Islamand Masuri Othman, “VLSI

Implementation of Discrete Wavelet Transform (DWT) for Image

Compression 2nd International Conference on Autonomous Robot stands

Agents Palmerston North, New Zealand, December 13-15, 2004.

[24] J. Torresen, J.W. Bakke, and L. Sekanina, “Efficient recognition of speed

limit signs”, in Processing of 7th IEEE International Conference on

Intelligent Transportation Systems (ITSC2004), 2004.

[25] Samhouri,“Surface Roughness in Grinding: Off-line Identification with

an Adaptive Neuro Fuzzy Inference system”,NAMRAC33-2005

conference,May24-27,Columbia, 2005.

[26] M. N. Do and M.Vetterli, "The contourlet transform: an efficient

directional multiresolution image representation," Image Processing,

IEEE Transactions, vol. 14, pp. 2091-2106, 2005.

[27] G. K. Kharate, A. A. Ghatol, P.P. Rege, “Image Compression Using

Wavelet Packet Tree ”, K.K.Wagh Institute of Engineering Education and

Research, Maharashtra, India, July 2005.

[28] Feng xiang Qiao, “Introduction to Wavelet, A Tutorial”, Workshop on

Wavelet Application in Transportation Engineering, January 09, 2005.

[29] Rajneesh Kumar, P.Kulashekar, B.Dhanasekar, B.Ramamoorthy,

“Application of digital image magnification for surface roughness

evaluation using machine vision”, International Journal of Machine Tools

& Manufacture 45 (2005) 228–234.

[30] Raymond H. Chan, Chung-Wa Ho and Mila Nikolova, “Salt-and pepper

noise removal by median-type noise detectors and detail preserving

regularization”, IEEE Transactions Image Processing, vol. 14, no. 10, pp.

1479-1485, October 2005.

131

[31] R. Garnett, T.Huegerich, C. K. Chui, and W. He, “A universal noise

removal algorithm with an impulse detector,” IEEE Trans. Image

Process., vol. 14, no. 11, pp. 1747-1754, Nov. 2005.

[32] Vincenzo Niola, Gennaro Nasti, Giuseppe Quaremba, “A problem of

emphasizing features of a surface roughness by means the Discrete

Wavelet Transform”, Journal of Materials Processing Technology 164–

165, 1410–1415, 2005.

[33] K.Muneeswaranal, Ganesan.B, S.Arumugam, K.RubaSoundar, “Texture

classification with combined rotation and scale invariant wavelet

features”, Pattern Recognition Society, Pattern Recognition 38, pp. 1495 –

1506, 2005.

[34] Bruno Josso, David R. Burton, Michael J.Lalor, “Texture orientation and

anisotropy calculation by Fourier transform and Principal Component

Analysis”, Mechanical Systems and Signal Processing 19, pp. 1152–1161,

2005.

[35] Biswajit Mishra and Pe ter Wilson, "Color edge detection hardware

based on geometric algebra” 3 r d European Conference on Visual Media

Production, 2006.(CVMP 2006),pp.115-121.

[36] Q. Miao and B. Wang, “A Novel Image Fusion Method Using Contourlet

Transform”, IEEE Proceedings of the 2006International Conference on

Communications, Circuits and Systems, vol. 1, pp. 548-552, 2006.

[37] A.Sumathi, and Dr.R.S.D.Wahida Banu, “Digital Filter Design using

Evolvable Hardware Chip for Image Enhancement”, IJCSNS

International Journal of Computer Science and Network Security, VOL.6

No.5A, May 2006.

132

[38] Akihiro Asahara, Munehiro Doi, Yumi Mori, Hiroki Nishiyama, and

Hiroki Nakano, “cell-broadband-engine-based real time wavelet

decomposition for HDTV video images and beyond”, IEEE Transactions,

2006.

[39] Markus Beermann, Adeel Jalil and Jens-Rainer Ohm, “Thresholded

Weighted Median Filters for Ringing Reduction in Processed Images”,

IEEE Transactions, 2006.

[40] Z. Vasicek and L. Sekanina, “Reducing the area on a chip using a bank of

evolved filters”, in L. Kang, Y. Liu, and S. Zeng (Eds.) Proceedings of

ICES 2007.

[41] Nader I.Rafla, “Evolvable Reconfigurable Hardware Framework for Edge

Detection”, IEEE Transactions, 2007.

[42] Soo Chang Kim, Tae Jin Kang, “Texture classification and segmentation

using wavelet packet frame and Gaussian mixture model”, Pattern

Recognition Society, Pattern Recognition 40, pp.1207–1221, 2007.

[43] C.Gonzalez-Garcia, J.H.Sossa-Azuela, E.M.Felipe-River on and

O.Pogrebnyak, “Image Retrieval based on Wavelet transform and Neural

Network classification”, Computation ySistemas Vol.11No.2, 2007, pp

145-156.

[44] Nader I.Rafla, Evaluable Reconfigurable hardware framework for edge

detection, IEEE transactions, 2007.

[45] Li Haosheng, WU Su , Hubert Kratz, “FFT and Wavelet-Based Analysis

of the Influence of Machine Vibrations on Hard Turned Surface

Topographies”, Department of Industrial Engineering, Tsinghua

University, Beijing 100084, China, Laboratory for Machine Tools and

Production Engineering (WZL), RWTH Aachen University of

Technology, Aachen 52074, Germany, August 2007.

133

[46] Sebastian Brol, Wit Grzesik, “Application Of Continuous Wavelet

Transform For Assessment Of Surface Roughness Profile After

Machining Of Hardened Aisi 52100 Steel”, Poland, 2007.

[47] A.Guruva Reddy, Dr.M.N.GiriPrasad and Dr.K.Sri Rama Krishna,

Reconfigurable circuit design using evolvable hardware chip for

illumination tolerant image enhancement, IEEE transactions, 2008.

[48] BoZhang, JalalM.Fadili and JeanLucStarck, “Wavelets, Ridgelets and

Curvelets for Poisson Noise Removal”, IEEE Transactions on Image

Processing, vol.17, no.5, pp.1093-1108, 2008.

[49] SamiKhanfir, MohamedJemni, “Reconfigurable Hardware

Implementations for Lifting-Based DWT Image Processing Algorithms”,

International Conference on Embedded Software and Systems ICESS, in

IEEE Transactions 2008.

[50] Long zhou, xiao-jun tong, “application of two-dimension wavelet

transform in image process of pets in stored grain”, Proceedings of the

Seventh International Conference on Machine Learning and Cybernetics,

in IEEE Transactions, Kunming, 12-15 July 2008.

[51] Jie Li and Shitan Huang, “Adaptive Salt-&-Pepper Noise Removal: A

Function Level Evolution based Approach”, in NASA/ESA Conference

on Adaptive Hardware and Systems, IEEE Computer Society, 2008.

[52] V.R.Vijaykumar, D.Ebenezer and P.T.Vanathi, “Detail preserving median

based filter for impulse noise removal in digital images”, ICSP

Proceedings, 2008.

[53] S.Kother Mohideen, Dr. S.Arumuga Perumal, Dr. M.Mohamed Sathik,

“Image De-noising using Discrete Wavelet transform”, in IJCSNS

International Journal of Computer Science and Network Security, VOL.8

No.1, January 2008.

134

[54] Haidi Ibrahim, Nicholas Sia Pik Kong and Theam Foo Ng, “Simple

Adaptive Median Filter for the Removal of Impulse Noise from Highly

Corrupted Images”, IEEE Transactions on Consumer Electronics,

Vol. 54,No. 4, November 2008.

[55] Deng Xiuqin, Xiong Yong Peng Hong, “A new kind of weighted median

filtering algorithm used for image Processing”, International Symposium

on Information Science and Engineering, IEEE Transactions, 2008.

[56] ZhiguoBao, Takahiro Watanabe, “A New Approach for Circuit Design

Optimization using Genetic Algorithm”, in International SOC Design

Conference, IEEE Transactions, 2008.

[57] S.M.W.Masra, M. S.Muhammad, R. Sapawi, “The Effect of Input

Limiting on Linear and Nonlinear Filters for the Removal of Impulsive

Noise”, in IEEE International Conference on Signal and Image Processing

Applications, 2009.

[58] Denis K. Kuykin, Vladimir V. Khryashchev, Ilya V. Apalkov, “An

improved switching median filter for impulse noise removal”, in IEEE

Transactions, 2009.

[59] Ch.Ravi Kumar, S.K.Srivathsa, “EHW Architecture for Design of

Adaptive Median Filter for Noise Reduction”, European Journal of

Scientific Research, ISSN 1450-216X Vol.36 No.3, pp 473-479, 2009.

[60] Du-xian Nie, You-Wei Wen, Shao-mei Fang, “Super-resolution Image

Reconstruction for Gaussian plus Salt-and-Pepper Noise Removal”, IEEE

Transactions, 2009.

[61] S. Balasubramanian, S. Kalishwaran, R. Muthuraj, D. Ebenezer, V. Jay

raj, “An Efficient Non-linear Cascade Filtering Algorithm for Removal of

High Density Salt and Pepper Noise in Image and Video sequence”,

international conference on “control, automation, communication and

energy conservation -2009”, 4th-6th June 2009.

135

[62] Tamas Raikovich, Bela Feher,“Application of Partial Reconfiguration of

FPGAs in Image Processing”, IEEE Transactions, 2009.

[63] B.Dhanasekar, B.Ramamoorthy, “Restoration of blurred images for

surface roughness evaluation using machine vision”, Tribology

International, Elsevier, 2009.

[64] Xiaoh Wang, “Intelligent Modeling and Predicting Surface Roughness in

End Milling”, Fifth International Conference on Natural Computation,

China, 2009.

[65] Jean-Luc Starck, Fionn Murtagh, Emmanuel J. Candès and David L.

Donoho, “Gray and Color Image Contrast Enhancement by the Curvelet

Transform”, IEEE Transactions on Image Processing, Vol. 12, No 6, , pp.

709-716, 2009.

[66] Melkamu. H. Asmare, Vijanth S. Asirvadam and Lila Iznita, “Multi-

Sensor Image Enhancement and Fusion for Vision Clarity Using

Contourlet Transform”, International Conference on Information

Management and Engineering (ICIME 2009), pp. 352-356, April 2009.

[67] Melkamu H. Asmare, Vijanth S. Asirvadam, Lila Iznita and Ahmad

Fadzil M. Hani, “Image Enhancement by Fusion in Contourlet

Transform”, International Journal on Electrical Engineering and

Informatics - Volume 2, Number 1, 2010.

[68] Chenguang Yan and Yujing Liu, “Application of Modified Adaptive

Median Filter for Impulse Noise”, International Conference on Intelligent

Control and Information Processing, Dalian, China, August 13-15, 2010.

[69] Wan Bao-cheng, Wang Tian-e, Zhou Tian-tian, “The Mathematical

Programming Problem of Total Variation Image Denoising Model”, IEEE

Transactions, 2010.

136

[70] Donglei Li, Zhemin Duan, MengJia,“New Method Based on Curvelet

Transform for Image Denoising”, International Conference on Measuring

Technology and Mechatronics Automation, IEEE Transactions, 2010.

[71] Panchao Wu, Zongyi Wang, “The Image Edge Detection Algorithm based

on Wavelet Denoising and Mathematics Morphology”, IEEE

Transactions, 2010.

[72] Zhengyang Guo, Wenbo Xu，Zhilei Chai, “Image Edge Detection Based

on FPGA”, Ninth International Symposium on Distributed Computing

and Applications to Business, Engineering and Science, 2010.

[73] Chih-Yuan Lien, Pei-Yin Chen, Li-Yuan Chang, Yi-Ming Lin and Po-Kai

Chang, “An Efficient Denoising Chip for the Removal of Impulse Noise”,

in IEEE Transactions, 2010.

[74] Shigong Yu, M. Omair Ahmad, M. N. S. Swamy, “Video Denoising

Using Motion Compensated 3-D Wavelet Transform With Integrated

Recursive Temporal Filtering”, IEEE transactions on circuits and systems

for video technology, vol. 20, no. 6,June 2010.

[75] Yulin Zhang, Xia Zhu, “Image De-Noising Algorithm Study and

Realization Based on Wavelet Analysis”, IEEE Transactions, 2010.

[76] Yu Wei-bo, Wang Yan, Pang Bai-mei, xu Zhi-jun, “An Improved

Threshold De-Noising Algorithm Based on Inter-Scale Dependency of

wavelet”, International Conference on Computer, Mechatronics, Control

and Electronic Engineering (CMCE), 2010.

[77] Davide Anastasia and Yiannis Andreopoulos, “Linear Image Processing

Operations with Operational Tight Packing”, IEEE signal processing

letters, Vol. 17, NO. 4, April 2010.

137

[78] Smaïl Akkoul, Roger Ledee, Remy Leconge, and Rachid Harba, “A New

Adaptive Switching Median Filter”, IEEE signal processing letters, IEEE

Transactions, 2010.

[79] Zhijun Pei, Qingqiao Tong, Lina Wang, Jun Zhang, “A Median Filter

Method for Image Noise Variance Estimation”, Second International

Conference on Information Technology and Computer Science, 2010.

[80] S. Deivalakshmi and P. Palanisamy, “Improved Tolerance based Selective

Arithmetic Mean Filter for Detection and Removal of Impulse Noise”, in

5th International Conference on Industrial and Information Systems,

ICIIS 2010, Jul 29 - Aug 01, 2010, India.

[81] K.Aiswarya, V.Jayaraj, D.Ebenezer, “A new and efficient algorithm for

the removal of high density salt and pepper noise in images and videos”,

in Second International Conference on Computer Modeling and

Simulation, 2010.

[82] S. Huang and J. Zhu, “Removal of salt-and-pepper noise based on

compressed sensing”, Electronics letters 19th August 2010 Vol. 46No. 17.

[83] Nan Ni, Yan-bin Zhang, Li-xin Jia, Wen-wen Cai, “A Pre-processing

Method based on the Wavelet Threshold De-noising Technique for the

Key Variables of Pulverized-coal Concentration”, IEEE Transactions,

2010.

[84] Zhe Liu, Huanan Xu, “Image Denoising using Contourlet and Two-

Dimensional Principle Component Analysis”, IEEE Transactions, 2010.

[85] Jiafu Jiang, Jing Shen, “An Effective Adaptive Median Filter Algorithm

for Removing Salt & Pepper Noise in Images”, IEEE Transactions, 2010.

[86] Nafisuddin Khan, K.V.Arya, Manisha Pattanaik, “An Efficient Image

Noise Removal and Enhancement Method”, IEEE Transactions, 2010.

138

[87] Siamak Rasoolzadeh, Roohollah Abdipour, “Low Power Implementation

of a Wavelet Based Noise Reduction System”, in 2nd International

Conference on Signal Processing Systems (ICSPS), 2010.

[88] Chuanxin Wang, Cheng Shao, and Yu Han, “Wavelet De-Noising

Double-Threshold Optimization Method and Its Application”, 8th IEEE

International Conference on Control and Automation Xiamen, China,

June 9-11, 2010.

[89] Le Zhang, Jing-long Yan，Dong-tao Li, “Application of Wavelet

Threshold Denoising Method in Signal Pre-processing for Blast

Vibration”, 3rd International Congress on Image and Signal Processing

(CISP), 2010.

[90] Chuanjun Song, Bingkun Gao, Lingling Kan, Hongwei Liang, “Image

Enhancement Based on Improved Genetic Algorithm and Lifting Wavelet

Method”, IEEE Transactions, 2010.

[91] Mrs.Punam U.Chati, “Framework for FPGA –Based Floating Point

Discrete-Wavelet Transform Computation Algorithm”, Second

International Conference on Computer and Network Technology, IEEE

Transactions, 2010.

[92] Marivi Tello Alonso, Carlos Lopez-Martinez, Jordi J. Mallorqui and

Philippe Salembier, “Edge Enhancement Algorithm Based on the Wavelet

Transform for Automatic Edge Detection in SAR Images”, in IEEE

transactions on Geoscience and remote sensing, 2010.

[93] Ming Tian, Hao Wen, Long Zhou, Xinge youl, “Image denoising using

multi-scale thresholds method in the wavelet domain”, Proceedings of the

2010 International Conference on Wavelet Analysis and Pattern

Recognition, Qingdao, 11-14 July 2010.

139

[94] Jiao Feng, Xie Yonghua, Xing Guowen, Naixue Xiong, Mei Yuan,

“Image Enhancement and Denoise Based on Structure Self-Similarity and

Wavelet Transform Coefficients”, IEEE Transactions, 2010.

[95] Ming Hao, Xingbo Sun, “A modified Retinex Algorithm based on

Wavelet Transformation”, in Second International Conference on

Multimedia and Information Technology, IEEE Transactions, 2010.

[96] Ke Ding, “Wavelets, Curvelets and Wave Atoms for Image Denoising”,

3rd International Congress on Image and Signal Processing (CISP), 2010.

[97] Chih Hsing Lin, Jia Shiuan Tsai and Ching Te Chiu, “Switching bilateral

filter with a texture/noise detector for universal noise removal”, IEEE

Transactions, 2010.

[98] Daniel Llamocca and Marios Pattichis, “Real-time Dynamically

Reconfigurable 2-D Filter banks”, IEEE Transactions, 2010.

[99] Emerson Carlos Pedrino, Jose Hiroki Saito, Valentin Obac Roda,

“Architecture for binary mathematical morphology reconfigurable by

genetic programming”, IEEE transactions, 2010.

[100] Jan Kloub, PetrHonzik and Martin Danek, “Reconfigurable Hardware

Objects for Image Processing on FPGAs”, IEEE Transactions, 2010.

[101] Tripti Jain, Prashant Bansod, C. B. Singh Kushwah and Mayenk

Mewara,“Reconfigurable Hardware for Median Filtering for Image

Processing Applications”, Third International Conference on Emerging

Trends in Engineering and Technology, IEEE Transactions, 2010.

[102] Zhijie Chen, Jihong Shen, Libin Guo, “A Wavelet Method based on

goodness of Fit test for roughness of Micro-EDM”, Proceedings of the

2010 IEEE International Conference on Information and Automation,

Harbin, China, June (20-23) 2010.

140

[103] Anil A.Patil, JyotiSinghai, “Image denoising using Curvelet transform: an

approach for edge preservation”, Journal of Scientific & Industrial

Research, vol.69, pp.34-38, 2010.

[104] Tripti Jain, Prashant Bansod, C.B.Singh Kushwah and Mayenk Mewara,

“Reconfigurable Hardware for Median Filtering for Image Processing

Applications”, IEEE transactions, 2010.

[105] ZheLiu, HuananXu, “Image Denoising using Contourlet and Two-

Dimensional Principal Component Analysis”,IEEE Proceedings,2010.

[106] Zhenman Fang, Donglei Yang, Weihua Zhang, Haibo Chen and Binyu

Zang, “A Comprehensive Analysis and Parallelization of an Image

Retrieval Algorithm”, IEEE Transactions, 2011.

[107] S. Esakkirajan, T. Veerakumar, Adabala N. Subramanyam, and C. H.

PremChand, “Removal of High Density Salt and Pepper Noise through

Modified Decision Based Unsymmetric Trimmed Median Filter”, IEEE

signal processing letters, VOL. 18, NO. 5, May 2011.

[108] Chen Cong-ping, Wang Jian, Qin Wu, Dong Xiao-gang, “A New

Adaptive Weight Algorithm for Salt and Pepper Noise Removal”, IEEE

Transactions, 2011.

[109] H. S. Bhadauria, Dr.M.L.Dewal,“Performance Evaluation of Curvelet and

Wavelet based Denoising Methods on Brain Computed Tomography

Images”, proceedings of ICETECT, in IEEE Transactions, 2011.

[110] K. Suganya, Dr.V.Nagarajan, “Efficient Run-time Task Allocation in

Reconfigurable Multiprocessor System-On-Chip with Network-On-Chip”,

International Conference on Computer, Communication and Electrical

Technology – ICCCET 2011, 18th & 19th March, 2011.

141

LIST OF PUBLICATIONS

International Journals:

[J1] P.Sivakumar, S.Ravi, “Image Enhancement using evolved reconfigurable

filter cores” International Journal of Computer Science and Network

Security, Vol.12, No.2, pp 123-127, February 2012.

[J2] P.Sivakumar, S.Ravi, “Performance of wavelet, Contourlet and 2D PCA

Transforms for image Denoising” CiiT International Journal of Digital

Image Processing,Vol.4,No.7,pp 386-391,April 2012.

[J3] P.Sivakumar, S.Ravi, “Vector Quantization Based Image Compression”

International Journal of Innovative Technology and Exploring

Engineering, Vol.1, No.1, pp 89-94, June 2012.

142

CURRICULUM VITAE

Mr. SIVAKUMAR.P was born in 1983 at Vellore, Tamil Nadu, India. He

obtained his DCT (Diploma in Computer Technology) in 2002 from Sri

Venkateswara Polytechnic College, Vellore, B.E (Electronics and

Communication Engineering) in 2005 from Priyadarshini Engineering College,

Vaniyambadi and M.Tech (Applied Electronics) in 2007 from the Dr.MGR

Educational and research institute University, Chennai. He has 7 years of

teaching experience and currently working as Assistant Professor,

ECE department, Kingston Engineering College, Katpadi. His area of interest

includes Digital Signal Processing and Digital Image Processing. He is a

member of IAENG, IACSIT, CSTA and Life member of ISTE.