iosr-JEEE   International Conference on Advances in Engineering & Technology – 2014 (ICAET-2014)

Abstract: Light weight cryptography (LWC) is an emerging research area which has to deal with the trade-off among security, cost, and performance. In this paper we present the idea and list some types of LWC algorithms. Hummingbird is a novel ultra lightweight cryptographic algorithm targeted for resource constrained devices like RFID tags, smart cards and wireless sensor nodes. The hybrid model of Hummingbird is explained keeping the constraint devices in mind and thus resulting in an easier software implementation. The paper presents the algorithms for the encryption as well as decryption process and shows some simulation results performed on Xilinx. Keywords: Lightweight cryptography, resource constrained devices, Hummingbird, RFID

[1] K. Finkenzeller, RFID-Handbook: Fundamentals and Applications inContactless Smart Cards and Identification. John Wiley and Sons, 2003. [2] ―Advanced Encryption Standard (AES),‖ National Institute of Standards and Technology (NIST), Federal Information Processing Standards (FIPS) Publication 197, November 2001. [3] M. Feldhofer, J. Wolkerstorfer, and V. Rijmen, ―AES Implementation on a Grain of Sand,‖ Information Security, IEE Proceedings, vol. 152, no. 1, pp. 13–20, 2005. [4] J. Daemen and V. Rijmen, The Design of Rijndael. Springer Verlag, Berlin, 2002. [5] ―Data Encryption Standard (DES),‖ National Institute of Standards and Technology (NIST), Federal Information Processing Standards (FIPS) Publication 46-3, October 1999. [6] I. Verbauwhede, F. Hoornaert, J. Vandewalle, and H. D. Man, ―Security and Performance Optimization of a New DES Data Encryption Chip,‖ IEEE Journal of Solid-State Circuits, vol. 23, no. 3, pp. 647–656, 1988. [7] K. T. Akashi Satoh, Sumio Morioka and S. Munetoh, ―A Compact Rijndael Hardware Architecture with S-Box Optimization,‖ in ASIACRYPT 2001, ser. LNCS, vol. 2248. Springer-Verlag, 2001, pp. 239 – 254. [8] S. Kumar, C. Paar, J. Pelzl, G. Pfeiffer, and M. Schimmler, ―Breaking Ciphers with COPACOBANA - A Cost-Optimized Parallel Code Breaker,‖ in Workshop on Cryptographic Hardware and Embedded Systems —CHES 2006,Yokohama, Japan. Springer Verlag, 2006.

Abstract: The paper presents an optical fiber ring structure consisting of interconnecting nodes connected using optical links. Optical ring networks communication are often confronted with the problem of routing and wavelength assignment. To eliminate the routing problem a simple unidirectional ring network with 8 nodes along with controller node is considered. The overview of ARTIFEX tool used to model the system has been presented. The simulation results have been shown in support of the work. Keywords : ARTIFEX , object, place, transition.

Artifex 4.4 Getting Started, ARTIS Software Corporation. Artifex 4.4 User Manual, ARTIS Software Corporation. Artifex 4.4 Reference Manual, ARTIS Software Corporation. 0.Gerstel, R. Ramaswami, and G. Sasaki, "Benefits of Limited Wavelength Conversion in WDM Ring Networks"(1997) 0.Gerstel and S. Kutten, "A dynamic RWA algorithm in a wavelength-routed all-optical network with wavelength converters"(2003)

Abstract: The digital signal processing has contributed in solving problems such as constructive interference, electrical echo, environmental noise, atmospheric noise, etc.Adaptive filters can be used to solve such problems. Nowadays FPGA systems are replacing dedicated programmable digital signal processor (PDSP) system due to their flexibility and large bandwidth, resulting from their parallel architecture. This paper presents implementation of adaptive noise canceller for cancelling noise signals present in speech signal. Least mean square algorithm is used for adaption of filter coefficients. The adaptive noise cancellation system is implemented in VHDL and tested for cancelling noise in speech signals. The simulation results of VHDL designed digital adaptive filter is performed and analyzed on basis of signal to noise ratio (SNR), Mean square error (MSE) convergence speed and tracking ability.

Keywords: Adaptive filtering, LMS algorithm, Noise cancellation, VHDL Design, Signal to noise ratio (SNR), Convergence Speed.

[1]L.J.Eriksson, M.C.Allie, and C.D.Bremigan," Active Noise Control using Adaptive digital signal processing," in proc ICASSP, New York,2004 [2] Simon Haykin. "Adaptive Filters Theory" Pearson Education. [3]Dimitris .G.Manolakis, V .K.Ingle and stepen M.kogon," Statistical and Adaptive Signal Processing". [4] C.Mosquera, J.A. Gomez "Adaptive filter for active noise control", Sixth international conference on sound and vibration Copenhagen, Denmark. [5]Colin H.Hansen "Understanding Active Noise Cancellation "IOS Press-2002

Abstract: This research Paper describes an automation of grinder using fuzzy logic. The rules base receives two input values Quantity and Material Type, fires the rule, and gives the output in terms of Range as defuzzifiers. This research paper work will increases the capability of fuzzy logic control system in process of automation of Grinder with potential benefits. In this paper, we represented a new idea to control the Range (Speed) of grinding, so that it can operate on its optimal speed as well as save electricity. Simulation is carried out with the help of MATLAB.

Keywords: Blender, Fuzzy logic control, Grinder, MATLAB

http://www.google.com/patents/US1480914 Constantin von Altrock, Fuzzy Logic and NeuroFuzzy Applications Explained (2002), Kipphan, Helmut (2001), Handbook of print media: technologies and production methods (Illustrated ed.). Springer. pp. 130–144. ISBN 3-540-67326-1.

Abstract: Specialists diagnose the neuromuscular diseases using visual inspection of the recorded Electromyogram (EMG) of the patients and compare their shape and key points to the standard ones. This paper represent the review on implementation of EMG classification of recorded signals from bicep muscles. The signals are collected from various patient group like normal, mayopathic and nueropathic during 25%, 50% and 75% muscles contraction. This recorded signals is then processed to extract some predefined features as input to the nueral network. The time and frequency based extracted features are use to train the nueral network. The trained nueral network will classify these signals using decompositioning the EMG signals.

Keywords : Electromyogram(EMG), motor unit action potentials, neural networks, chaos, BPNN(Back Propogation neural network), RNN(Radial Basis function neural network ).

[1] R. S. LeFever and C. J. DeLuca, "A procedure for decomposing the myoelectric signal into its constituent action potentials: I.Technique, theory and implementation," IEEE Trans. Biomed. Eng., vol. BME-29,pp. 149–157, Mar. 1982. [2] "A procedure for decomposing the myoelectric signal into its constituent action potentials: II. Execution and test for accuracy," IEEE Trans. Biomed. Eng., vol. BME-29, pp. 158–164, Mar. 1982. [3] "Unsupervided Pattern Recognition for the Classification of EMG Signals" IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 46, NO. 2, FEBRUARY 1999. [4] "EMG Diagnosis using Neural Network Classifier with Time Domain and AR Features" ACEEE Int. J. on Electrical and Power Engineering, Vol. 01, No. 03, Dec 2010. [5] "Optimization of Neural Network for Efficient EMG Signal Classification" 978-1-4673-0862-5/12/$31.00 ©2012 IEEE. Books: [6] "Clinical Neurophysiology" UK Mishra & JKalita Second editon Elsvier Publications 2004. Proceedings Papers: [7] "A study of back-propagation and radial basis neural network on emg signal classification" Proceeding ofthe 6th International Symposium on Mechatronics and its Applications (ISMA09), Sharjah, UAE, March 24-26,2009.

Abstract: There is an important role for information theory in the development of new wireless networked systems. Wireless networking is a very different and significantly more complex field compared to point-to-point wireless systems that have been addressed so successfully by information theorists. Whereas obtaining performance characterizations that are as simple and as compact as, e.g., channel capacity in point-to-point problems may be unrealistic, information theoretic approaches might help identify tradeoffs and relationships among key variables. That is, the ideas that inspired Shannon to develop the foundation of information theory have a very relevant role to play in the context of wireless networks, at least in meaningful asymptotic regimes in signal to noise ratio (SNR) and in the size of the network. Indeed, researchers with an information-theoretic background have made headway in establishing some fundamental perimeters of this field that is experiencing a continuing growth with new applications.

[1] DavidTse, Professor, University of California at Berkeley Information Theory at the Extremes

[2] JohnTreichler, Chief Technical Officer, Applied Signal Technology, Inc.The Impact of Economics and Technological Trends on New Wireless Services [3] DipankarRaychaudhuri, Professor, Rutgers University Research Challenges in Wireless Communication and Networking.

Abstract: Channel Estimation is very important in any wireless communication .In this paper the performance evaluation of different types of PSK modulations with three different channel estimation methods in OFDM system for wireless communication for slow fading channel is compared. Comb type channel estimation is use. Channel is estimated at pilots position which are all one's for all OFDM block and complete channel is estimated with linear interpolation. Performance of estimated channel is compared with result of known channel at the receiver.

Keywords: OFDM, Comb type Channel estimation, LS, RLS, QRD, PSK Modulation, interpolation

[1] Sinem Coleri Mustafa Ergen Anuj Puri and Ahmad Bahai, "Channel estimation techniques based on pilot arrangement in OFDM systems," [2] S. Haykin, "Adaptive Filter Theory, 3rd ed". NJ: Prentice-Hall, 1996. [3] Report on Hierarchical pipelining and folding of QRD-RLS adaptive filters and its application to digital beamforming [4] Mathuranathan Viswanathan, "Simulation of Digital Communication Systems Using Matlab" [5] Sinem Coleri, Mustafa Ergen, Anuj Puri Ahmad Bahai, "Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems" [6] Saqib Saleem1, Qamar-ul-Islam, "Channel Estimation using Adaptive Filtering for LTE-Advanced", IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 2, May 2011 [7] Jan-Jaap van de Beek at al, "On Channel Estimation In OFDM Systems", In Proceedings of Vehicular Technology Conference (VTC Ô95), vol. 2, pp. 815-819, Chicago, USA, September 1995. [8] Christian Rohde, Wolfgang Gerstacker, Bernhard Schmidt, and Wolfgang Koch, "Comparison of One-Dimensional Adaptive Channel Estimation Techniques for OFDM Systems"

Abstract: Face recognition has now become an important area of research in Computer vision and image analysis and is being worked upon extensively with newer techniques emerging out and claiming higher accuracy rate of recognition than before. Each technique comprises possible factors like posing, illumination, occlusion, expression variations etc. that may affect the recognition rate, but very few consider the variations caused on human face due to ageing. This paper surveys the prominent published literature of last eight years to analyze and summarize the work done so far on age invariant face recognition or verification system and evaluate them on various scales like computational speed, accuracy, performance consistency in intrinsic and extrinsic conditions. The motivation for this paper is to provide a review of current age invariant models available in literature and estimate the best one that fulfills all features and conditions.

Keywords: Age invariance, Computer vision, extrinsic conditions, Face recognition, and intrinsic conditions

[1]. S. Gong, S. J. McKenna, and A. Psarrou., Dynamic Vision: From Images to Face Recognition: Imperial College Press (World Scientific Publishing Company), 2000. [2]. K. Balci and V. Atalay, "PCA for Gender Estimation: Which Eigenvectors Contribute?" in Proceedings of Sixteenth International Conference on PatternRecognition, Vol.3. Quebec City, Canada, 2002, pp. 363-366. [3]. B. Moghaddam and M. H. Yang , "Learning Gender with Support Faces," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.24, pp.707-711, 2002.

Abstract: Linear and nonlinear filters have been proposed earlier for the removal of impulse noise; however this often brings about blurring which results in distorted edges and poor quality. Therefore the necessity to preserve the edges and fine details during filtering is the challenge faced by researchers today. A new non-linear algorithm for the restoration of gray scale and color images that are highly corrupted by salt and pepper noise is proposed in this paper. The proposed algorithm consists of two phases. In the first phase, the noise corrupted pixels is detected based on direction index based impulse detector. In the second phase, the detected pixels are filtered using unsymmetric trimmed median filter. Simulation results demonstrate that the proposed algorithm is better than traditional median-based filters and is particularly effective for the cases where the images are very highly corrupted.

Keywords : direction index basedimpulse detector,impulse noise, median-based filter, gray scale image, unsymmetric trimmed median filter

[1] J. Astola and P. Kuosmaneen, Fundamentals of Nonlinear Digital Filtering. Boca Raton, FL: CRC Press, 1997
[2] P.E.Ng and K.K. Ma,"A switching median filter with boundary discriminative noise detection for extremely corrupted images,"IEEE Trans. Image Process., vol. 15, no. 6, pp. 1506–1516, Jun. 2006
[3] Z. Wang, D. Zhang. "Progressive switching median filter for the removal of impulse noise from highly corrupted images", IEEE Trans. Circuits Systems – II, vol. 46, pp. 78-80, Jan. 1999
[4] K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision based algorithm for removal of high density impulse noise,"IEEE Signal Process. Lett., vol. 14, no. 3, pp. 189–192, Mar. 2007
[5] V. Jayaraj and D. Ebenezer, "A new switching-based median filtering scheme and algorithm for removal of high-density salt and pepper noise in image,"EURASIP J. Adv. Signal Process., 2010
[6] K. Aiswarya, V. Jayaraj, and D. Ebenezer, "A new and efficient algorithm for the removal of high density salt and pepper noise in images and videos," Second Int. Conf. Computer Modeling and Simulation,May 2010, pp. 409–413
[7] S. Esakkirajan, T. Veerakumar, A. N. Subramanyam, and C. H. PremChand, "Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter," IEEE Signal Process. Lett., vol. 18, no. 5, pp. 287–290, May 2011
[8] Raymond H. Chan, Chung-Wa Ho, and Mila Nikolova ," Salt-and-Pepper Noise Removal by Median-type Noise Detectors and Detail preserving Regularization", IEEE Trans. Image Processing, vol. 14, no. 10, pp.1479–1485, Oct. 2005
[9] S.Zhang and M.A.Karim, "A new impulse detector for switching median filters,"IEEE Signal Process. Lett., vol. 9, no. 11, pp. 360–363,Nov. 2002.

Abstract: Because of nature of job, unhealthy social habits and voice abuse, people are subjected to risk of voice problems It is well known that most of speech disorders causes changes in the acoustic voice signals [9].In the recent year the trend towards automated analysis of pathological noise signal has gain momentum. The awkwardness of analog equipment has simulated development of digital computer techniques for processing and analysis of pathological speech signal in patient care system. The above filter design techniques & prepossessing of speech signal can be used in any speech processing application.In this paper voices of patients are taken and they are preprocessed. In prepossessing Speech signal is passed through Moving Average (M.A) filter, High pass (H.P) filter for removal of noise & then framing and windowing is done. This preprocessed output can be used for pathological voice recognition, speech identification, speaker identification & many more application.

Keywords -Framing, High-Pass Filter, Moving Average Filter, Pathological Speech Signal,Windowing.

[1] Manjot Kaur Gill, Vector," Quantization based Speaker identification",International Journal of Computer Application (0975-8887) Volume 4-No.2,pp1-4July 2010. [2] J.W.Picone, "Signal modeling techniques in speech recognition",Proceedings of the IEEE, Vol.81, No.9, Sept.1993. [3] Lotfi Salhi,Talbi Mouradand Adnene Cherif, "Voice Disorders Identification Using Multilayer Neural Network", The International Arab Journal of Information Technology Volume 7-No.2, pp.177-185 April 2010. [4] Antanas Lipeika, Joana Lipeikiene, Laimutis Telksnys, "Development of Isolated speech Recognition System", INFORMATICA, 2002, Vol 13, No.1, 37-46, 2002. [5] Milan Sigmund, "Voice Recognition by Computer", (Tectum Verlag publication, pp no20-22). [6] John G.Proakis, Dimitris, G.Manolakis, "Digital Signal Processing. Principles, Algorithm and Applications",(Prentice Hall India, pp.309, Third Edition). [7] Orzechowski, A. Izworski, R. Tadeusiewiez, K. Chmunzynska, P. Radkowski, I. Gotkowska, "Processing of pathological change in speech caused by Dysarthria", IEEE Proceedings of 2005 International symposium on intelligent signal processing & communication system, pp 49-52, Dec 13-16, 2005. [8] Martinez Cesar E, Refiner Hugo L, "Acoustic Analysis of speech for detection of Laryngeal pathologies", IEEE proceeding of the 22nd Annual EMBS international conference Chicago IL, pp.2369-2372, 2000. [9] M.Hariharan,M.P.Paulraj,Sazali, Aacob, "Time = Domain Features and Probabilistic Neural Network for the Detection of Vocal Fold Pathology", Malaysian journal Of Computer Science, Vol (23) 2010, pp. 60-67. [10] Marcelo de Oliveira Rosa,Jose Carlos Pereira and Marcos Gellet, "Adaptive Estimation of Residue Signal for Voice Pathology Diagnose",IEEE Transaction on Biomedical Engineering , Vol.47, No.1, Jan.2000.

Abstract: Visual cryptography Scheme (VCS), an emerging cryptography technology, uses the characteristics of human vision to decrypt encrypted images without requirement of complex computation. Naor and Shamir proposed the basic model of visual cryptography for binary images. In this work, a new technique for visual cryptography of gray-level image is proposed, which uses first halftone visual cryptography technique to convert a given gray level image into an approximate binary image. Then, the existing visual cryptography scheme for binary image is applied to accomplish creation of shares. On the similar grounds based on the method proposed by Naor and Shamir, where the cryptography technique is based on the (2 out of n shares ) we extend the same idea to implement the Visual Cryptography for color images by considering the ( k out of n shares ) where more than two shares are used to extract the information which is visually cryptographed. In order to improve the quality of image ordered dithering and half toning techniques are used. The primary limitations of the above methods are that it has the poor detail rendition and the contour artifacts. In order to overcome the above limitations we use the new scheme known as "Space Filling curve ordered dithering"( SFCOD). The overall effect of the proposed method is the achievement of visual encryption and decryption functions for gray scale images, where the quality of decrypted image is better compared to the decrypted image obtained by VCS using Space-filling curve order dither technique. This is shown by experimental results based on the objective measurement technique.

Keywords: 1.VCS, 2. HVS, 3. SFCOD, 4. Halftone, 5. Dithering

[1] M. Naor, A. Shamir, Visual cryptography, Advances in Cryptology Eurocrypt '94, Lecture Notes in Computer Science,Springer, Berlin, 1995, Vol. 950, pp. 1–12. [2] Verheul, Van Tilborg, Construction and Properties of k out of n visual secret sharing scheme Designs Codes Cryptography, 1997, Vol. 11, pp.179–196. [3] C. Lin, T.H. Tsai, Visual cryptography for gray-level images by dithering techniques, Pattern Recognition Letters 24, 2003,pp.349–358. [4] Yuefeng Zhang, Space-Filling Curve Ordered Dither, Elsevier, Computer & Graphics, 1998, Vol.22, No. 4, pp. 559±563.

Abstract: Content based image retrieval (CBIR) is a challenging problem due to large size of the image database, difficulty in recognizing images, difficulty in devising a query and evaluating results in terms of semantic gap, computational load to manage large data files and overall retrieval time. Feature extraction is initial and important step in the design of content based image retrieval system. Feature extraction is a means of extracting unique and valuable information from the image. These features are also termed as signature of image. Similar images should have similar signature. Feature extraction of the image in the database is done offline therefore it does not contribute significantly in computational complexity. In this paper, we present two features color and texture extraction algorithms. Humans tend to differentiate images based on color, therefore color features are mostly used in CBIR. Color histogram is mostly used to represent color features but it cannot entirely characterize the image. Color Histogram is also rotation invariant about the view axis. Regularity, directionality, smoothness and coarseness are some of the texture properties perceived by human eye. Gabor filter, a tool for texture feature extraction has proved to be very effective in describing visual content via multi-resolution analysis. Texture feature extraction based on Gabor filter is presented.

Keywords – Content Based Image Retrieval, Feature Extraction, Color Histogram, Gabor Filter.

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R. Gonzales, R. E. Woods, "Digital Image Processing," 2nd Ed., New Jersey Prentice Hall, 2002.
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Abstract: Today we need faster devices with high voltage and high switching frequency capability, generally used Silicon-based devices are not able to meet these requirements as they need costly cooling systems, so we need much faster devices like Wide band-gap based semiconductors. These devices have superior physical properties that offer multiple advantages like lower intrinsic carrier concentration , higher electric breakdown field ,higher thermal conductivity and large saturated electron drift velocity which is suitable for faster devices with high voltage and high switching frequency.

[1] S. Bernet, .Recent developments of high power converters for industry and tractionapplications,. IEEE Trans. Power Electron., vol. 15, pp. 1102.1117, Nov. 2000. [2]http://www.ecn.purdue.edu/WBG/SiC Data Bank, Introduction, Basic Studies,Device Research: From the Purdue.s Wide Band Gap Semiconductor Device in Electrical and Computer Department, America. [3]http://www.ifm.liu.se/matephys/new_page/research/sic/Chapter2.html#2.2. [4]http://www.grc.nasa.gov/WWW/SiC/SiCReview.html: Philip G. Neudeck, NASALewis research Center, M.S. 77-1, 21000, Brook Park road, Cleveland, OH 44135. [5]http://www.ecn.purdue.edu/WBG/DeviceResearch/PowerDevices/Index.html: From the Purdue's Wide Band Gap Semiconductor Device Research in Electrical andComputer Department, America.

Abstract: Iris recognition is one of the most accurate identity verification system. Since its initial introduction by J. Daughman, many methods have been proposed to enhance the performance. Many methods have been proposed to feature extraction by many researchers. We present an overview of the latest research of feature extraction of iris recognition. We present the latest development in terms of accuracy, relaxibility and complexity explaining advances to solve problems existing of feature extraction stage o iris recognition system.

Keywords: Biometric, iris recognition, Gabor Wavelet, DCT, Haar Transform, LBP, PCA, Log Gabor Wavelet, feature extraction.

[1] Pravin S. Patil(April 2012)," The Comparison of Iris Recognition using Principal Component Analysis, Log Gabor and Gabor Wavelets", International Journal of Computer Applications (0975 – 8887) Volume 43– No.1. [2] J. G. Daugman (1993), "High confidence visual recognition of persons by a test of statistical independence", IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11), 1148–1161.

[3] J. Daugman (1994), "Biometric Personal identification System based on iris analysis", US patent no. 529160. [4] P Kovesi. (1999), "Image features from phase congruency.", Videre Journal of Computer Vision Research, 1(3), 1–27. [5] P. Kovesi. (2003)," Phase congruency detects corners and edges.",In DICTA, Sydney. [6] Dolly Choudhary, Shamik Tiwari, Ajay Kumar Singh," A Survey: Feature Extraction Methods for Iris Recognition". International Journal of Electronic Communication & Computer Technology(IJECCT) Volume 2 Issue 6(Nov 2012)pp. 275-279. [7] R. V. Patil, K. C. Jondhale (2009)," Content Based Image Retreival Based on Phase Congruency Via Log Gabor Wavelet Filters", Proceedings of ICCVGIVP 2009. Nagpur, pp 84-85.

Abstract: This paper presents a detailed analysis of recent work in power aware routing protocols in Mobile Ad hoc Networks (MANETs). Mobile nodes have limited battery life time, mobile networks should use battery power more resourcefully to increase the network life. The purpose of a routing protocol for MANETs is to support the transmission of packet from a source to all the destinations while trying to use the available bandwidth efficiently in the presence of continuous topology changes. However, offering power aware routing is a difficult and challenging task. This paper elaborates the review of various power aware routing protocols in addition to diverse metrics responsible for power optimization.

Keywords: MANET, Network Simulator-2, Power-aware routing, Reactive protocol, Routing Protocols..

[1] M. Mohammed, Energy Efficient Location Aided Routing Protocol for Wireless MANETs, International Journal of Computer Science and Information Security, vol. 4, no. 1 & 2, 2009.
[2] Y. B. Ko, and N. H. Vaidya, Location-Aided Routing (LAR) in Mobile Ad hoc Networks, Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking, 1998.
[3] The CMU Monarch Project, The CMU Monarch Extensions to the NS Simulator, URL:http://www.monarch.cs.cmu.edu/.Page accessed on February 20th, 2010.
[4] Divya sharma, Ashwini kush ,Power and mobility aware protocol for adhoc network, International Journal of Engineering and Technology, Vol.3, No.2, April 2011.
[5] S. Doshi, T. X. Brown, Minimum Energy Routing schemes in Wireless Ad hoc networks, IEEE INFOCOM 2002.

Abstract: India is a country where agriculture is the backbone of economy. It is need of hour to estimate agricultural production based upon its sown area, which deems to be not achievable manually every year. The underlying reason behind is the existing facilities and mechanism is inadequate to achieve the same. However, with the advent of state of the art technologies in Remote Sensing and GIS, it is quiet easy to predict acreage of agricultural product in advance. In order to identify the land use by the crops, classification is the important task to be done. Still, it's a real challenge to get better classification accuracy. Various supervised and unsupervised classification techniques are introduced by the researchers. The reviews of those techniques with their respective problems and prospects, is highlighted in the paper. The main objective is to find out the efficient classification technique that applied on multi-spectral remote sensing data for agricultural applications and to explore futuristic research in this domain.

Keywords: Remote sensing images, supervised classification , unsupervised classification,GIS

1] Haihui Wang, Junhua Zhang, Kai Xiang, Yang Liu, " Classification of Remote Sensing Agricultural Image by Using Artificial Neural Network" , Intelligent Systems and Applications, 2009. ISA 2009, IEEE workshop. .
[2] Jiejun HUANG, Yanbin YUAN, "An Approach Based on Decision Tree to Agricultural Land Grading" ,IEEE Computer Design and Applications (ICCDA), 2010 International Conference on (Volume:2 ) [3] Krishna Mohan Buddhiraju and Imdad Ali Rizvi "Comparison of CBF, ANN and SVM Classifier for Object Based Classification of High Resolution Satellite Image", IGARSS 2010 [4] S.Manthira Moorthi, Indranil Misra, Rajdeep Kaur, Nikunj P Darji and R. Ramakrishnan "Kernel based learning approach for satellite image classification using support vector machine" ,IEEE 2011. [5] Wei Yao and Min Han, "Remote Sensing Image Classification with Parameter optimized Support Vector Machine based on Evolutionary Computation", Fourth international Workshop on Advanced Computational Intelligence Wuhan, Hubei, China; October 19-21, 2011 [6] Swarnajyoti Patra and Lorenzo Bruzzone, "A Novel SOM-Based Active learning technique for classification remote sensing image with SVM." ,IEEE , IGARSS 2012 [7] S. N. Omkar, Nikhil Ramaswamy,J. Senthilnath, "Gene Expression Programming- Fuzzy Logic Method For Crop Type Classification", IEEE, 2012 Sixth International Conference on Genetic and Evolutionary Computing