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i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 2

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Volume 2 Issue 2 May - July 2013

Article

Low Cost 160×130 Uncooled Infrared Sensor Array

M. Vilasini* , Yuva Priya V**

* Assistant Professor, ECE Department, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India.

** M.E, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India.

Vilasini.M., and Priya,Y.V. (2013). Low Cost 160×130 Uncooled Infrared Sensor Array. i-manager’s Journal on Embedded Systems, 2(2), 1-5. https://doi.org/10.26634/jes.2.2.2370

Abstract

This paper gives Readout Integrated Circuit (ROIC) design required for infrared detector in Forward Looking Infrared (FLIR)camera. This design is based on monolithically fabricated 160 x 130 array of uncooled infrared detector. This design provides uniform output over a wide range of temperature and the output is specified in terms of quantum efficiency, specific detectivity and Noise Equivalent differential Temperature (NEdT). This design is fabricated for a high volume low cost production application.

References

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[2]. Paul Jerram, David Burt, Neil Guyatt, Vincent Hibon, Joel Vaillant, Yann Henrion “Back-thinned CMOS Sensor Optimization”, e2v technologies, Waterhouse Lane, Chelmsford, CM1 2QU, UK e2v semiconductors SAS, Avenue de Rochepleine, Saint-Egrève, France.

[3]. Bhan,R.K., Saxena,R.S. Jalwania,C.R. and Lomash. S.K. (2009). “Uncooled Infrared Microbolometer Arrays and their Characterization Techniques”, Defence Science Journal, Vol. 59, No. 6, November , pp. 580-589.

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[5]. Eun Sik Jung, Young Seok Bae and Man Young Sung . (2012). Design of Current-Type Readout Integrated Circuit for 160 ×120 Pixel Array Applications, Journal of Electrical Engineering & Technology Vol. 7, No. 2, pp. 221~224.

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[7]. Selim Eminoglu, Deniz Sabuncuoglu Tezcan, M. Yusuf Tanrikulu, Tayfun Akin, (2003) “Low-cost uncooled infrared detectors in CMOS process”, Sensors and Actuators A 109, 102–113.

[8]. Joeri De Vos, Anne Jourdain, Wenqi Zhang, Koen De Munck, Piet De Moor, Antonio La Manna, (2011). The road towards fully hybrid CMOS image sensors, International Symposium on Microelectronics, October .

[9]. A. Rogalski, (2009). “Infrared Detectors for the Future”, Optical and Acoustical Methods in Science and Technology, Vol. 116.

[10]. Antoni Rogalski, (2002). “Infrared detectors: an overview” Infrared Physics & Technology 43 ,187–210.

[11]. Selim Eminoglu, Mahmud Yusuf Tanrikulu and Tayfun Akin, (2008). Journal of Microelectromechanical Systems, “A Low-Cost 128 × 128 Uncooled Infrared Detector Array in CMOS Process,” Vol. 17, No. 1, February .

[12]. Deniz Sabuncuoglu Tezcan, Selim Eminoglu and Tayfun Akin,(2002) “A Low-Cost Uncooled Infrared Microbolometer Detector in Standard CMOS Technology”, IEEE transactions on electron devices, Vol. 50, No. 2, February .

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Research Paper

License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method

Siddharth Choubey* , G. R. Sinha**

* Assistant Professor (CSE), Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India.

** Professor (ETC) & Associate Director, Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India.

Choubey,S., and Sinha.G.R. (2013). License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method. i-manager’s Journal on Embedded Systems, 2(2), 6-16. https://doi.org/10.26634/jes.2.2.2371

Abstract

The detection of license plate location is the most important part of a vehicle license plate recognition process. This paper compares the performance of various methods for detecting license plate. We have introduced a novel recursive algorithm for labeling and finding the regions and detected the plate location on the basis of the pixel count method after calculating the area of the regions and removing those region that are not likely to be license plate. Experiment results give better performance and achieved up to 100 percent localization accuracy.

References

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[15]. Yusuf A. Syed , Sarfraz, M.(2005). “Color Edge Enhancement Based Fuzzy Segmentation of License Plates” , Published in: IV '05 Proceedings of the Ninth International Conference on Information Visualisation Pages 227 - 232, IEEE Computer Society Washington, DC, USA ©2005 ISBN:0-7695-2397-8doi>10.1109/IV.33

[16]. Jing-Ming Guo, Yun-Fu Liu, (2008).“License Plate Localization and Character Segmentation With Feedback Self-Learning and Hybrid Binarization Techniques” IEEE Transactions on Vehicular Technology, Vol 57, No. 3, MAY pp:1417-1424.

[17]. I-Chen Tsai, Jui-Chen Wu, Jun-Wei Hsieh, and Yung-Sheng Chen, “Recognition of Vehicle License Plates from a Video Sequence” IAENG, International Journal of Computer Science,volume36:issue1, IJCS_36_1_04[OnlineFullText]

[18]. Ali Tahir, Hafiz Adnan Habib, M. Fahad Khan, (2010)” License Plate Recognition Algorithm for Pakistani License Plates” Canadian Journal on Image Processing and Computer Vision Vol.1,No.2,April .

[19]. Osslan Osiris Vergara Villegas, Daniel González Balderrama. (2009). Humberto de Jesús Ochoa Domínguez and Vianey Guadalupe Cruz Sánchez, “License Plate Recognition Using a Novel Fuzzy Multilayer Neural Network” International Journal Of Computers Issue 1, Volume3,pp:31-40.

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[23]. Shi, X.,Zhao, W. and Shen,Y.,(2005). “Automatic license plate recognition system based on color image processing,” in Lecture Notes on Computer Science, Vol. 3483, O. Gervasi et al., Eds. New York: Springer Verlag,pp.1159–1168.

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[27]. Feng Wang, Lichun Man, Bangping Wang, Yijun Xiao, Wei Pan, Xiaochun Lu.(2008). ”Fuzzy-based algorithm for color recognition of license plates” Published in: Journal Pattern Recognition Letters archive Volume29 Issue7, May, pp-1007-1020.

[28]. Kim, K. I., Jung, K. and Kim, J. H. “Color texture-based object detection: An application to license plate localization,” in Lecture Notes on Computer Science, vol. 2388, S.-W.Lee and A. Verri, Eds.NewYork:Springer-Verlag,pp.293–309.

[29]. Cano, J. and Perez-Cortes, J. C.(2003). “Vehicle license plate segmentation in natural images,” in Lecture Notes on Computer Science, Vol. 2652,F. J. Perales et al., Eds. New York: Springer-Verlag,pp.142–149.

[30]. Llorens, D., Marzal, A., Palazon, V. and Vilar, J. M. “Car license plates extraction and recognition based on connected components analysis and HMM decoding,” in Lecture Notes on Computer Science, Vol.3522,J.S.

[31]. Broumandnia, A. and Fathy, M. (2005). “Application of pattern recognition for Farsi license plate recognition,” presented at the ICGST Int. Conf. Graphics,Vision and Image Processing (GVIP), Dec.[Online].Available: http://www.icgst.com/gvip /v2/P1150439001.pdf

[32]. Aleksander Król; Teresa Pamula.(2009). ”Localization of vehicle license plates in images using fuzzy logic and morphological operations Transport Problems : an International Scientific Journal Issn:18960596 Eissn: Vol 4 Issue:1 pages/rec.No:95-101

[33]. SerkanOzbay, and Ergun Ercelebi,(2005). Automatic Vehicle Identification by Plate Recognition, World Academy of Science, Engineering and Technology, 9, LD AC

[34]. Dubey, P.,(2005). “Heuristic approach for license plate detection ” Advanced Video and Signal Based Surveillance, AVSS 2005. IEEE Conference on 15-16 Sept. 2005 Nat. Sci. & Technol. Dev. Agency, Nat. Electron. &Comput. Technol. Centre, Thailand pp 366-370

[35]. Zimic, N., Ficzko,J., Mraz, M. and Virant, J.(1997). “The fuzzy logic approach to the car number plate locating problem,” in Proc.IIS, pp.227–230.

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[38]. Nijhuis, J. A. G.,TerBrugge, M. H, Helmholt, K. A, Pluim, J.P.W., Spaanenburg, L.,Venema, R. S, Westenberg, M.A. (1995). “Car license plate recognition with neural network and fuzzy logic“ In proceedings of IEEE international conference on Neural Networks Conference, Vol 5, pp 2232-2236, PerthAustrali.

[39] Kahraman, F.,Kurt, B. and Gökmen, M.(2003), “License plate character segmentation based on the gabor transform and vector quantization,” in Lecture Notes on Computer Science, vol. 2869, A. Yazici and C. Sener, Eds. New York: Springer- Verlag, pp.381–388

[40]. Becerikli, Y. ,Olgac, A.V., Sen, E. Coskun, F.(2007). ,” Neural Network Based License Plate Recognition System “This paper appears in:Neural Networks, 2007. IJCNN 2007. International Joint Conference on:12-17,pp:3057-3061

[41]. Adorni, G., Cagnoni, S.,Gori, M., and Mordonini, M.(2001). “Access control system with neuro-fuzzy supervision,”in Proc.Conf.Intell.Transp.Syst.,pp.472-477.

[42]. Yoshimori, S.,Mitsukura, Y.,Fukumi, M. and Akamatsu, N.(2003). “License plate detection using hereditary threshold determine method,” in Lecture Notes in Artificial Intelligence, vol. 2773, V. Palade, R. J. Howlett, and L. C. Jain, Eds. New York: Springer-Verlag,pp. 585–593.

[43]. Cui, Y. and Huang, Q. (1998).“Extracting characters of license plates from video sequences,” Mach. Vis. Appl., Vol.10, no.5/6,pp.308–320,.

[44]. Duan, T. D., Hong Du, T. L. , Phuoc, T. V. and Hoang, N.V.(2005). “Building an automatic vehicle license plate recognition system,”in Proc. Int. Conf. Comput. Sci. RIVF, , pp.59–63.

[45]. Chu-DucNguyen, Ardabilian, M.,Liming Chen,(2008) “Real-time license plate localization based on a new scale and rotation invariant texture descriptor ” Intelligent Transportation Systems, . ITSC 2008. 11th International IEEE Conference on 12-15, pp.956–961.

[46]. Hsieh, C.T.,Juan, Y.S. and Hung, K.M.(2005) “Multiple license plate detection for complex background,” in Proc. Int. Conf.AINA., vol.2,pp.389–392.

[47]. Kim, D.S., and Chien, S.I.(2001). “Automatic car license plate extraction using modified generalized symmetry transform and image warping,” in Proc.ISIE, 2001, pp. 2022–2027.

[48]. TerBrugge, M. H.,Stevens, J. H.,Nijhuis, J. A. G. and Spaanenburg, L.(1998). “License plate recognition using DTCNNs,” in Proc. IEEE Int. Workshop Cellular Neural Netw. and Appl., pp. 212–217.

[49]. Chacon, M. I. and Zimmerman, A.(2003). “License plate location based on a dynamic PCNN scheme,” in Proc. Int.Joint Conf. Neural Network.,vol.2, pp.1195–1200.

[50]. Kim, K. K. ,Kim, K. I., Kim, J. B. and Kim, H. J.(2000.) “Learning- based approach, for license plate recognition,” in Proc. IEEE Signal Process. Soc. Workshop, Neural Netw. Signal Process.,vol.2,pp.614–623.

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Research Paper

Performance Analysis of Signal Characteristics of MODFET

V. Ganesan* , K.S. Shaji**

* Research Scholar, Department of Electronics and Telecommunication Engineering, Sathyabama University, Chennai, India.

** Principal, Rajaas International Institute of Technology for Women, Nagercoil, India.

Ganesan.V., and Shaji.K.S. (2013). Performance Analysis of Signal Characteristics of MODFET. i-manager’s Journal on Embedded Systems, 2(2), 17-22. https://doi.org/10.26634/jes.2.2.2372

Abstract

This work addresses the scalability of power performance of AlGaAs/GaAs MODFET (modulated-Doping Field Effect Transistor) with large gate periphery, as necessary for microwave power devices. High-frequency large signal characteristics of AlGaAs/GaAs MODFET have been studied for devices with gate widths from 0.2 to 1 mm. 1-dB gain compression occurred at input power levels varying from -1 to +10dBm as the gate width increased, while gain remained almost constant at ~17dB. Output power density was maximum (1.3W/mm) for devices with 0.6mm gates and maximum output power (29.9dBm) occurred in devices with 1mm gates, while power-added-efficiency remained almost constant at ~30%.We also present a model for the I-V characteristics of MODFET's. In this paper, an analytic velocity-field model is used. To more accurately describe the physical characteristics of MODFET's the model of this paper is divided into two regions (the linear region and the saturation region), being continuous at the pinchoff voltage, and includes the diffusion component in addition to the drift component of current. Using this model, the simulated I-V characteristics are in excellent agreement with the experimental data.

References

[1]. Wu, Y.F. et al.,(1997) “Short-Channel Al0.5Ga0.5N/ GaN MODFETs with power density >3W/mm at 18GHz”, Electronics Letters, Vol. 33, N.20, p 1742-1743

[2]. Sheppard, T.S. at al.(1998).,"High power microwave AlGaAs/GaAs HEMTs on Silicon Carbide", in Late News 56th Annual Device Research Conference, avail. Athttp://schof.colorado.edu/~drc/drc1998/lateprog.htm

[3]. Nguyen, N.X. et al,(1998). “Device characteristics of scaled AlGaAs/GaAs MODFETs“, Electronics Letters, Vol.34, N.8, p 811-812.

[4]. Nguyen, N.X et al.(1997).” AlGaAs/GaAs MODFET with 80GHz fMAX and >100V gate-drain breakdown voltage”, Elec Electronics Letters, Vol.33, No.4, 1997,p 334-335

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Research Paper

A Comparaison Between Specific And Generic Fuzzy Expert System For Athlete ECG Analysis

Najar Yousra* , Raouf Ketata, Mekki Ksouri*

* Department of Informatics, Higher Institute of Informatics Tunis (ISI), Tunisia.

Department of Electrical Engineering, National Institute of Applied Sciences and Technologies (INSAT), Tunisia.

* Department of Electrical Engineering , National School of engineering of Tunis (ENIT), LASC, Tunisia.

Yosra,N., Ketata,R., and Ksouri,M. (2013). A Comparaison Between Specific and Generic Fuzzy Expert System for Athlete ECG Analysis. i-manager’s Journal on Embedded Systems, 2(2), 23-30. https://doi.org/10.26634/jes.2.2.2373

Abstract

Nowadays, heart disease prediction is a challenge to modern technologies. An Electrocardiogram (ECG) is a preferred tool that could help in making decision about heart conditions. However, uncertainties, that affect sensors measurements in ECG, raise the challenge. This paper describes automatic analysis of Electrocardiographic recordings (ECGs), through the analysis of variables using fuzzy inference systems. Concerned ECGs are specifically those of competitive football players. Hence, variables characterizing ECG are determined from Pre Competition Medical Assessment (PCMA) form imposed by FIFA. Two decision making fuzzy systems are developed. In the first hand, specific Fuzzy Expert System (FES) for ECG analysis is presented to decide about the state of concerned player. In another hand, generic fuzzy expert system, already used in industrial diagnosis and in video surveillance, is presented for the same purpose. Finally, a comparison between two systems is detailed to highlight the efficiency of using generic fuzzy expert system.

References

[1]. Drezner, J. A. (2012), Standardised criteria for ECG interpretation in athletes: a practical tool. Br J Sports Med, 46.

[2]. Adeli, A. & Neshat, A. (2010). A Fuzzy Expert System for Heart Disease Diagnosis. Proceedings of the International Multi Conference of Engineering and Computer Scientist, Hong Kong.

[3]. Barman, M. & Choudhur. (2012). A Fuzzy Rule Base System for the diagnosis of heart disease. International Journal of Computer Applications, 57(7), 46-53.

[4]. Najar, Y. Ketata, r. & Ksouri, M. (2013). Fuzzy Expert System for Residual Analysis. Journal of Information Organization, 3(1), 23-35.

[5]. Najar, Y. Ketata, r. & Ksouri, M. (2013). A study on Fuzzy Expert System for surveillance. International Journal of Advanced Computer Science and Applications, SAI, 4(8).

[6]. Novruz, A. Serhat, T. & l Saritas, I. (2007). Design of fuzzy expert system for determination of coronary heart disease risk. International Conference on Computer System and Technologies.

[7]. Retrieved from http://www.learntheheart.com/ecg review/ecginterpretation- tutorial/qt-interval/

[8]. Ephzibahl, E.P. & Sundarapandian, V. (2012). A neuro Fuzzy expert system for heart disease diagnosis. Computer science & Engineering: An International Journal, 2(1), 17-23.

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Research Paper

VLSI Based Low Power Hardware Design Using DistributedArithmetic (DA) Centered 2d Adam7 Transform For The Proposed Image Compression Algorithm

L. Vignesh* , C. N. Marimuthu, J. Joseph Lynn*

- Department of Electronics & Communication Engineering, Maharaja Engineering College, Avinashi,Tirupur.

Department of Electronics & Communication Engineering, Nandha Engineering College(Autonomous), Erode.

Vignesh.L., Marimuthu.C.N., and Lynn,J.J. (2013). VLSI Based Low Power Hardware Design Using Distributed Arithmetic (da) Centered 2D ADAM7 Transform for the Proposed Image Compression Algorithm. i-manager’s Journal on Embedded Systems, 2(2), 31-37. https://doi.org/10.26634/jes.2.2.2374

Abstract

The need for an efficient technique for compression of images is ever increasing because, the raw images need large amounts of disk space where seem to be a big disadvantage during transmission and storage. Even though, there are so many compression techniques already present, a better technique which is faster, memory efficient and simple, surely suits the requirements of the user. We have planned to design the hardware design flow of Distributed Arithmetic (DA) based 2-D Adam7 algorithm for the proposed image compression algorithm. Accordingly to, an effective 2-D Adam7 algorithm will be performed on input image using well-known Distributed Arithmetic (DA) technique, which exploits the LUT-based FPGA structure to build multiplier-less filter bank, the main component in a Adam7 structure. After computing the Adam7 algorithm, the suitable Adam7 co-efficient is selected and then, applied DPCM (Differential Pulse-Code Modulation) that is a transformation for increasing the compressibility of an image. Finally, the transformed image is given to Huffman-encoder that is designed by merging the lowest probable symbols in such a way that, the images will get compressed. For implementation, the DA-based Adam7 Algorithm is modeled in Simulink and tested. The Verilog source code is developed for the algorithm. All the modules are simulated in Xilinx tool and the final design is verified with Verilog test benches. The final design is implemented in Xilinx Atlys Spartan 6 FPGA Kit.

References

[1]. Shoushun Chen, Amine Bermak and Yan Wang.(2011). “A CMOS Image Sensor With On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm”, IEEE Transactions On Very Large Scale Integration (VLSI) Systems, Vol. 19, No. 4.

[2]. Chao-Tsung Huang, Po-Chih Tseng And Liang-Gee Chen.(2005) "VLSI Architecture for Forward Discrete Wavelet Transform Based on B-spline Factorization", Journal of VLSI Signal Processing, 40, 343-353, 2005

[3]. Chao-Tsung Huang, Po-Chih Tseng, and Liang-Gee Chen,(2005). "Analysis and VLSI Architecture for 1-D and 2-D,Discrete Wavelet Transform", IEEE Transactions On Signal Processing, Vol. 53, No. 4.

[4]. Xixin Cao, Qingqing Xie, Chungan Peng, Qingchun Wang, Dunshan Yu,(2006).”An Efficient VLSI Implementation of Distributed Architecture for DWT", Multimedia Signal Processing, IEEE 8th Workshop on, pp. 364 - 367, Oct. 2006.

[5]. Kai Liu, Ke-Yan Wang, Yun-Song Li and Cheng-Ke Wu,(2007). "A novel VLSI architecture for real-time line-based wavelet transform using lifting scheme", Journal of Computer Science and Technology, Vol. 22, No. 5.

[6]. Wang Chao and Cao Peng,(2010). "Efficient Architecture for 2-Dimensional Discrete Wavelet Transform with Novel Lifting Algorithm", Chinese Journal of Electronics, Vol.19, No.1,Mohsen Amiri Farahani, Mohammad Eshghi,

[7]. Longa, P.,Miri, A. and Bolic, M.(2008). "Implementing a New Architecture of Wavelet Packet Transform on FPGA", Proceedings of the 8th WSEAS International Conference on Acoustics & Music: Theory & Applications, Vancouver, Canada, June 19-21.

[8]. Maria A. Trenas, Juan Lopez, Emilio L. Zapata,(2000).“FPGA Implementation of Wavelet Packet transform with Reconfigurable Tree Structure”, Euro micro Conference. Proceedings of the 26th Volume 1, 5-7 Sept. 2000, pp. 244 - 251 Vol.1.

[9]. Kumar Gupta, A.,Dyer, M., Hirsch, A.,Nooshabadi, S., Taubman, D.(2005) "Design of a single chip block coder for the EBCOT engine in JPEG2000", Proceedings of the 48th Midwest Symposium on Circuits and Systems, pp: 63 - 66.

[10]. Hemasundara Rao, C. and Madhavi Latha, M. (2009). "A Novel VLSI Architecture of Hybrid Image Compression Model based on Reversible Blockade Transform", World Academy of Science, Engineering and Technology 52.

[11]. Isa Servan Uzun, Abbes Amira,(2005) "Real-time 2-D wavelet transform implementation for HDTV compression", Real-Time Imaging 11 151-165.

[12]. Jagadish H. Pujar, Lohit M. Kadlaskar .(2010). “A New Lossless Method of Image Compression And Decompression Using Huffman Coding Techniques”, Journal of Theoretical and Applied Information Technology, Vol. 15, No.1.

i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 2

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Volume 2 Issue 2 May - July 2013

Low Cost 160×130 Uncooled Infrared Sensor Array

M. Vilasini* , Yuva Priya V**

* Assistant Professor, ECE Department, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India. ** M.E, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India.

Vilasini.M., and Priya,Y.V. (2013). Low Cost 160×130 Uncooled Infrared Sensor Array. i-manager’s Journal on Embedded Systems, 2(2), 1-5. https://doi.org/10.26634/jes.2.2.2370

Abstract

References

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License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method

Siddharth Choubey* , G. R. Sinha**

* Assistant Professor (CSE), Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India. ** Professor (ETC) & Associate Director, Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India.

Choubey,S., and Sinha.G.R. (2013). License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method. i-manager’s Journal on Embedded Systems, 2(2), 6-16. https://doi.org/10.26634/jes.2.2.2371

Abstract

References

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Performance Analysis of Signal Characteristics of MODFET

V. Ganesan* , K.S. Shaji**

* Research Scholar, Department of Electronics and Telecommunication Engineering, Sathyabama University, Chennai, India. ** Principal, Rajaas International Institute of Technology for Women, Nagercoil, India.

Ganesan.V., and Shaji.K.S. (2013). Performance Analysis of Signal Characteristics of MODFET. i-manager’s Journal on Embedded Systems, 2(2), 17-22. https://doi.org/10.26634/jes.2.2.2372

Abstract

References

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A Comparaison Between Specific And Generic Fuzzy Expert System For Athlete ECG Analysis

Najar Yousra* , Raouf Ketata**, Mekki Ksouri***

Yosra,N., Ketata,R., and Ksouri,M. (2013). A Comparaison Between Specific and Generic Fuzzy Expert System for Athlete ECG Analysis. i-manager’s Journal on Embedded Systems, 2(2), 23-30. https://doi.org/10.26634/jes.2.2.2373

Abstract

References

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VLSI Based Low Power Hardware Design Using DistributedArithmetic (DA) Centered 2d Adam7 Transform For The Proposed Image Compression Algorithm

L. Vignesh* , C. N. Marimuthu**, J. Joseph Lynn***

*-*** Department of Electronics & Communication Engineering, Maharaja Engineering College, Avinashi,Tirupur. ** Department of Electronics & Communication Engineering, Nandha Engineering College(Autonomous), Erode.

Vignesh.L., Marimuthu.C.N., and Lynn,J.J. (2013). VLSI Based Low Power Hardware Design Using Distributed Arithmetic (da) Centered 2D ADAM7 Transform for the Proposed Image Compression Algorithm. i-manager’s Journal on Embedded Systems, 2(2), 31-37. https://doi.org/10.26634/jes.2.2.2374

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* Assistant Professor, ECE Department, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India.

** M.E, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, India.

* Assistant Professor (CSE), Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India.

** Professor (ETC) & Associate Director, Faculty of Engineering and Technology, ShriShankaracharya Group of Institutions, Bhilai, India.

* Research Scholar, Department of Electronics and Telecommunication Engineering, Sathyabama University, Chennai, India.

** Principal, Rajaas International Institute of Technology for Women, Nagercoil, India.

Najar Yousra* , Raouf Ketata, Mekki Ksouri*

L. Vignesh* , C. N. Marimuthu, J. Joseph Lynn*

- Department of Electronics & Communication Engineering, Maharaja Engineering College, Avinashi,Tirupur.

Department of Electronics & Communication Engineering, Nandha Engineering College(Autonomous), Erode.