Publication for Volume-1 Issue-9, August 2016
Now a day in India here is automation in every field even in agriculture also. Appropriate ambient conditions are necessary for optimum plant growth, improved crop yields, and efficient use of water and other resources. Automating the data acquisition process of the soil conditions and various climatic parameters that govern plant growth allows information to be collected at high frequency with less labor requirement with the help of robot with high quality camera for leaf diseases detection using line follower image algorithm. Different types of sensors are used such as LM 35, humidity, soil fidelity and Light sensors for controlling and monitoring plant house. The Robot camera detects an image is in the form of JPEG, sends to ARM controller by using Zigbee Transmission theory in an long distance away from plants for plant health detection automatically and controlling action is done such as to control the motor drive by the SPDT relays also.
Keywords : Robot; camera; plant health; sensors; diseases; controlling; zigbee;
 Prof. K.V. Fale 1, Bhure Amit P 2, MangnaleShivkumar 3 PandharkarSuraj” Autonomous Farming Robot with Plant Health Indication” International Journal of Advanced Technology in Engineering and Science, Volume No.03, Issue No. 01, January 2015.  Schillaci G, Pennisi A, Franco F, Longo D "Detecting tomato crops in greenhouses using a vision based method" International Conference RAGUSA SHWA, Vol 1 ,pp.3-6 , September 2012  Yadav, S. P., Ibaraki, Y., & Gupta, S. D. (2010). “Estimation of the chlorophyll content of micro propagated potato plants using RGB based image analysis.” Plant Cell Tissue and Organ Culture, 100(2), 183-188.  M. Seelye, G. Sen Gupta, J. Seelye, & S. C. Mukhopadhyay (2010). Camera-in-hand Robotic system for Remote Monitoring of Plant Growth in a Laboratory. Proceeding of IEEE International Instrumentation and Measurement Technology Conference  Ciubotaru-Petrescu B, Chiciudean D, Cioarga R, StanescuD, ”Wireless Solutions for Telemetry in Civil Equipment and Infrastructure Monitoring”, 3rd Romanian-Hungarian Joint Symposium on Applied Computational Intelligence (SACI) May 25-26, 2006  Muhammad Ali Mazidi, Janice Gillispie Mazidi, Rolin D. Mc Kinlay , The 8051 Microcontroller & Embedded Systems, Pearson Education Inc. 2nd Edition, 2008.  SENSORS- The Journal of Applied Sensing Technology, Advanstar
A gear is a rotating machine part having cut tooth, which mesh with another toothed part in order to transmit torque. To design the spur gear to study the weight reduction and stress distribution for cast steel and composite materials. Gearing is one of the most critical components in a mechanical power transmission system, and in most industrial rotating machinery. The main objective of this research work is to introduce a new gear material for gear. EN32A, EN24 is selected for suitability analysis. Gears are the important part of any machine application like electric overhead travel, machine tool, automobile for power transmission. The main part of this research work is to identify the natural frequency and natural vibration modes of EN32A, EN24 gear and also the effect of change in mass of gear. This project is based on the topology optimization of the existing gear with the reduction of material from the gear and to reduce the total weight of the gear. F.E. Modelling shall be pursued for deriving analytical solution to the problem while physical experimentation would be done to offer inputs to the work and validate the model at the initial phase of work. Hyper Works is being considered as a CAE tool for Pre-processing, Solving and Post processing. The experiment would be performed on the physical setup for the existing/ benchmark case.
Keywords : Mass, Vibration, Material, EN32A, EN24, EN202, Modal Analysis
 Amit Aherwar, Md. Saifullah Khalid. “Vibration Analysis Techniques For Gearbox Diagnostic: An International Journal Of Advanced Engineering Technology” E-Issn 0976-3945.  Jianming Yang, “Vibration Analysis On Multi-Mesh Gear-Trains Under Combined Deterministic And Random Excitations”, Mechanism And Machine Theory 59 (2013) 20–33.  Zhonghong Bu, Geng Liu , Liyan Wu, “Modal Analyses Of Herringbone Planetary Gear Train With Journal Bearings” , Mechanism And Machine Theory 54 (2012) 99–115.  Marianne Mosher, Anna H. Pryor, David G. Lewicki, “Detailed Vibration Analysis Of Pinion Gear With Time-Frequency Methods”, Nasa/Tm-2003-212269.  Alexander Kapelevich Graco, “Geometry And Design Of Involute Spur Gears With Asymmetric Teeth”, Mechanism And Machine Theory 35(2000) 117–130.  Mitchell Lebold, Katherine Mcclintic, Robert Campbell, Carl Byington, And Kenneth Maynard, “Review Of Vibration Analysis Methods For Gearbox Diagnostics And Prognostics”, Proceeding Of The 54th Meeting Of Society For Machinery Failure Prevention Technology, Virginia Beach, Va,May 1-4,2000,P.623-634.  G.Dalipaz, A.Rivola and R.Rubini, “Gear Fault Monitoring: Comparison Of Vibration Analysis Techniques”, 2-I-40136 Bologna, Italy.  Jiri Tuma, “Gearbox Noise and Vibration Prediction and Control”, International Journal Of Acoustic And Vibration, Vol.14, No.2, 2009.  Abhilesh Warade, “Vibration Analysis Of Annular Disc With Periodic Uniform Radial Slots While Disc Is Clamped At Inner Edge And Free At Outer Edge” E-Issn 0976-3945.  Mr. K.S. Tanpure, “Vibrational Analysis Of Genset Silencer Using Fea & Fft Analyzer”. Issn: 2349-6193.  Mr. Ashwani Kumar, Himanshu Jaiswal, Rajat Jain, Pravin Patil “Free Vibration and Material Mechanical Properties Influence Based Frequency And Mode Shape Analysis Of Transmission Gearbox Casing”. Procedia Engineering 97(2014) 1097-1106.  Mr. Ashwani Kumar, Arpit Dwivedi, Vipul Paliwal, Rajat Jain, Pravin Patil “Free Vibration Analysis Of Al 2024 Wind Turbine Blade Designed For Uttarakhand Region Based On Fea”. Procedia Technology 147(2014) 336-347.  M. A. Chowdhury, Md. M. Helali: The Influence of Natural Frequency Of The Experimental Set-Up On The Friction Coefficient Of Stainless Steel-304. Tribology In Industry Vol 32, Pp.19-24 (2010).
Urban advancement is a noteworthy issue in metropolitan domains in the country, with enormous impact on economy, travel conduct, land utilize, and purpose behind uneasiness for some drivers. Bangalore today is a standout among the most taken care of urban communities in the country with the great improvement in the IT business and the increase in the amount of openings for work in the city. With the expansion in populace, there is a relating increase in number of vehicles in the city and enormous increment in the interest in area. In Bangalore there is a problem in extension for streets development and the need to utilize existing streets for smooth development of vehicles. These problems get to be compulsory for the organization to assure better parking facilities. Due to increase in the traffic, the waiting time at the signalized intersections increases. In order to minimize the waiting time, the PTV Vissim software is used and models were developed and proposals were made.
Keywords : Traffic volume, Traffic queue, Queue length, Queue delay, Signalized intersection, PTV Vissim
 Shuguo Yang, Xiaoyan Yang., “The Application of the Queuing Theory in the Traffic Flow of Intersection”, World Academy of Science, Engineering and Technology International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering Vol:8, No:6, 2014  Anusha, C. S., Ashish Verma, and G. Kavitha. "Effects of Two-Wheelers on Saturation Flowat Signalized Intersections in Developing Countries", Journal of Transportation Engineering, 2013.  Ahmad Sadegh and A. Essam Radwan, (1988) “Comparative Assessment Of 1985 Hcm Delay Model” Journal of Transportation Engineering, Vol. 114, No. 2, March, 1988.  Ali Payidar Akgungor and A. Graham R. BULLEN (2007), “A New Delay Parameter for Variable Traffic Flows at Signalized Intersections”, Turkish J. Eng. Env. Sci. 31 (2007), 61 – 70. ©T¨UB˙ITAK  P.S. Suresh, C .Krishna Kumar, and K. V. Krishna Roa (2004), Delay model for real time ATC in heterogeneous traffic conditions, Strategies in traffic engineering and management (STEM-2004) paper.  Lian Xue, Minghui Wu, Hui Yan., “Study of Vehicle Characteristics of Signalized Intersection based on Queuing Theory”, WSEAS TRANSACTIONS on MATHEMATICS, November 2010.  Hossain, M.. "Estimation of saturation flow at signalised intersections of developing cities: a micro-simulation modelling approach", Transportation Research Part A, 200102.  Guoqiang Zhang. "Study on Saturation Flow Rates for Signalized Intersections", 2009 International Conference on Measuring Technology and Mechatronics Automation, 04/2009.  Ragab M. Mousa (2002), “Accuracy of Stopped Delay Measured by Stopped-Vehicle Counts Method” Journal of Transportation Engineering, Vol. 128, No. 5, September 1, 2002. ©ASCE,  Kim, Sang-Ock, and R. F. Benekohal. "Comparison of Control Delays from CORSIM and the Highway Capacity Manual for Oversaturated Signalized Intersections", Journal of Transportation Engineering, 2005.  Pal, Sudipta, and Sudip Kr Roy. "Impact of Roadside Friction on Travel Speed and LOS of Rural Highways in India", Transportation in Developing Economies, 2016.  Sonu, Mathew, Ashish Dhamaniya, Shriniwas Arkatkar, and Gaurang Joshi. "Time occupancy as measure of PCU at four legged roundabouts", Transportation Letters, 2016.
Software architecture research has emerged over the past decade, as the fundamental study of the overall structure of software systems, particularly the relations among subsystems and components. Building the foundation for software architecture is the main focus of this paper. The paper started with developing an intuition for software architecture by appealing to several well-established architectural disciplines. Considering this intuition, a model of software architecture is presented that comprises of three components: elements, form, and rationale. The paper provides a classification of software architectures which turn out to be the foundation for the establishment of marketplaces for software components. The basis of component marketplace lies in the framework of key properties of software architecture. We can understand the development and scenario of software architecture research by examining the research paradigms used to establish its results.
Keywords : Software Architecture, Architectural Styles, Subsystem, Software elements
 Mary Shaw, the Coming-of-Age of Software Architecture Research, Institute for Software Research, International Carnegie Mellon University, 2001  Mary Shaw and Paul Clements, The golden age of software architecture, Institute for Software Research International School of Computer Science, February 2006  Devayne E.Perry and Alexander L.Wolf, Foundation for study of software architecture, Department of Computer Science University of Colorado October 1992  Robert T. Monroe, Andrew Kompanek, Ralph , David B. Garlan, Architectural Styles, Design Patterns, and Objects, Carnegie Mellon University, September 1996  Philippe B. Kruchten. The 4+1 view model of architecture. IEEE Software, 28(11):42–50, November 1995  Gerald Meszaros, Software architecture in BNR, In Proceedings of the First International Workshop on Architectures for Software Systems, 1995.  E.J. Chikofsky (Ed), Software Development Computer-aided Software Engineering, Technology Series, IEEE Computer Society Press, 1988.  F.C. Mish, Webster's Ninth New Collegiate Dictionary, Merriam Webster, Springfield, MA, 1983.  B.W. Boehm, Software Engineering Economics, Prentice-Hall, Englewood Cliffs, NJ, 1981.  D.E. Perry, The Inscape Environment, Proc. Eleventh Inter. Conf. on Software Engineering, Pittsburgh, PA, IEEE Computer Society Press, May 1989, pp. 2-12.  A Brief Survey of Software Architecture by Rikard Land (Department of Computer Engineering, Mälardalen University, Västerås, Sweden, February 2002)  Software Architecture: Foundation of a Software Component Marketplace by E. James Whitehead, Jr. Jason E. Robbins Nenad Medvidovic Richard N. Taylor (Department of Information and Computer Science University of California, Irvine, 1995)  Software Architecture Styles a Survey, Ashish Kumar, Computer Science and Engineering, February 2014  Mary Shaw and David Garlan, Software Architecture, Prentice Hall of India, 2004.
This paper tries to propose a solution for various issues that uncover while migrating the data from old legacy systems to new systems. Business organizations implement new Software Application System to replace the functionalities of their major processes by their old legacy systems from time to time. Data Migration is the procedure of relocating data from one framework then onto the other while changing the capacity, database or application. Complexities arise when there is a try to take the information (data) right from the legacy framework (system) and change or modify it to fit into the new framework (system). Mostly the structure and the data types of the old legacy systems are different in relation to the new system being implemented; the difference is simply not constrained to the table names, field names, properties or sizes. The types of databases are distinct, as also the entity relationships in the new framework may not compatible with the earlier legacy systems. To get the legacy data into its new application format, a certain number of modifications and transformations must take place. These modifications and transformations are known as 'Data Conversion'. During the implementation of new framework, the current structure which is being used by the old legacy system is taken into account and is mapped to the new framework being designed and implemented.
Keywords : Data Migration, Data Warehouse, Legacy, Issues, Systems
 Legacy System Data Conversion and Migration http://www.kmgin.com/Docs/White-Paper/data_migration.pdf  Consolidating Data from Diverse Legacy Systems http://www.cloveretl.com/sites/applicationcraft/files/files/solutions/data/Clover_Data_Migration_Case_Study.pdf  Data migration from old to new application http://www.gplivna.eu/papers/legacy_app_migration.htm  Data Migration Challenges and solution for successful implementation https://www.linkedin.com/pulse/20140918151302-65816706-data-migration-challenges-and-solution-for-successful-implementation
The objective of salient region detection is to separate salient region from entire image. This salient region detection framework consists of a structure-guided statistical textural distinctiveness approach. This approach includes the five main stages: i) image decomposition ii) textural representation, iii) texture modeling, iv) matrix construction, and v) saliency map computation. In the image decomposition stage, decomposition of image into structural image elements to learn a structure-guided texture model. In second stage, define a rotational-invariant neighborhood based texture feature model that represents the underlying textural characteristics of regions in a local manner. In texture modeling stage, Sparse texture modeling is done using structure-guided texture learning. In matrix construction stage, characterize all pair-wise statistical textural distinctiveness within the sparse texture model of the image and construct a textural distinctiveness matrix. In the final stage, the saliency of a region can be computed as the expected statistical textural distinctiveness of the region in the given image .The proposed approach has been extensively evaluated on images from MSRA-1000 datasets.
Keywords : Saliency, Salient region detection, Structure-guided
 L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis,", in Proc. IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 11, pp. 12541259, Nov. 1998.  J. Harel, C. Koch, and P. Perona, “Graph-based visual saliency,", in Advances in Neural Information Processing Systems 19. Cambridge, MA, USA: MIT Press, 2007.  X. Hou and L. Zhang, “Saliency detection: A spectral residual approach", in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2007, pp. 18.  R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,", in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2009, pp. 15971604.  M.-M. Cheng, G.-X. Zhang, N. J. Mitra, X. Huang, and S.-H. Hu, “Global contrast based salient region detection," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2011, pp. 409416.  F. Perazzi, P. Krahenbuhl, Y. Pritch, and A. Hornung, “Saliency filters: Contrast based filtering for salient region detection," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2012, pp. 733740.  X. Shen and Y. Wu, “A uni_ed approach to salient object detection via low rank matrix recovery," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2012, pp. 853860.  H. Jiang, J. Wang, Z. Yuan, Y. Wu, N. Zheng, and S. Li, “Salient object detection: A discriminative regional feature integration approach," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 2083 2090.  Q. Yan, L. Xu, J. Shi, and J. Jia, “Hierarchical saliency detection," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 1155 1162.  C. Yang, L. Zhang, H. Lu, K. Ruan, and M.-H. Yang, “Saliency detection via graph-based manifold ranking," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 31663173.  C. Scharfenberger, A. Wong, K. Fergani, J. S. Zelek, and D. A. Clausi, “Statistical textural distinctiveness for salient region detection in natural images," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 979986.  Christian Scharfenberger, Alexander Wong, Member, IEEE, and David A. Clausi,Senior Member, IEEE “Structure-Guided Statistical Textural Distinctiveness for Salient Region Detection in Natural Images" IEEE Transactions On Image Processing, VOL. 24, NO. 1, January 2015  R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Suesstrunk, SLIC superpixels compared to state-of-the-art superpixel methods, IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 11, pp. 22742282, Nov. 2012.
A chemically modified electrode was successfully fabricated by means of depositing a thin layer of Copper hexacyanoferrate (CuHCF) on an amine adsorbed gold nanoparticle graphite paraffin wax composite electrode using a new approach. The electrochemical characteristics of the modified electrode were studied using cyclic voltammetry and electrochemical impedance spectroscopy (EIS). The modified electrode was able to catalyze dopamine (DA) and moreover was able to eliminate the electrode fouling caused by the electrochemical oxidation of dopamine at the bare electrode.. However when the modified electrode was further covered with a Nafion membrane, the interference could be diminished. The catalytic current for oxidation of dopamine at the modified electrode increased linearly with a concentration range of 3.5 x 10-6 to 1.4 x 10-3 M. of dopamine with a correlation coefficient of 0.999. The limit of detection was found to be 1.2x10-7M. Based on S/N=3. Flow injection analysis technique was used for the determination of dopamine and it was found that the electrode produced excellent reproducible results.
Keywords : GNP; Copper hexacyanoferrate; Dopamine.
 Yoon J.K., Kim K.,. Shin K.S, Raman scattering of 4-Aminobenzenethiol sandwiched between Au nanoparticles and a macroscopically smooth Au substrate: effect of size of Au nanoparticles, J. Phys. Chem C 113 (2009) 1769 – 1774.  Zhang H., Wang G., Chen D., Lv X., Li J., A multifunctional biocide/sporocide and photocatalyst based on titanium dioxide (TiO2) codoped with silver, carbon, and sulfur, Chem. Mater. 20 (2008) 6543 - 6549.  Yamauchi Y., Takai A., Nagaura T., Inoue S., Kuroda K., Pt fibers with stacked donut like mesospace by assembling Pt nanoparticles: guided deposition in physically confined self-assembly of surfactants, J. Am Chem Soc 130 (2008) 5426 - 5427.  Luo X., Morrin A., Killard A.J.,. Smyth M.R, Application of nanoparticles in electrochemical sensors and biosensors. Electro analysis 18 (2006) 319 - 326.  Pingarron J.M, Sedeno P.Y., Cortes A.G., Gold nanoparticle-based electrochemical biosensors, Electrochim Acta 53 (2008) 5848 - 5466.  Pournaghi-Azhar M.H., Razmi-Nerbin H., Electroless preparation and electrochemistry of nickel-pentacyanonitrosylferrate film modified aluminum electrode, Electroanalysis 12 (2000) 209 - 215.  Cai C.X., Xue K. H., Xu S.M., Electrocatalytic activity of a cobalt hexacyanoferrate modified glassy carbon electrode toward ascorbic acid oxidation, J. Electroanal Chem 486 (2000) 111 - 118.  Garcia-Jareno J.J., Navarro J.J.,. Roig A.F, Scholl H., Vicente F., Impedance analysis of prussian blue films deposited on ITO electrodes, Electrochim Acta 40 (1995)1113 – 1119.  Malik M.A., Miecznikowski K., Kulesza P. J, Quartz crystal microbalance monitoring of mass transport during redox processes of cyanometallate modified electrodes: complex charge transport in nickel hexacyanoferrate films, Electrochim Acta 45 (2000) 3777 – 3784.  Neff V.D., Itaya K., Uchida I., Electrochemically of polynuclear transition metal cyanides: prussian blue and its analogues, Acc. Chem. Res. 19 (1986) 162 – 168.  Itaya K., Ataka T., Toshima S., Electrochemical preparation of a prussian blue analog: iron-ruthenium cyanide J. Am.Chem Soc. 104 (1982) 3751 – 3752.  Christensen P.A., Hamnett A., Higgins S.J. Soc, A study of electrochemically grown prussian blue films using fourier-transform infra-red spectra, J. Chem Dalton Trans (1990) 2233 – 2238.  Mortimer R. J.,. Rosseinsky Soc D. R, Iron hexacyanoferrate: spectrochemical distinction and electrodeposition sequence of soluble (K+ containing) and insoluble (K+ free) prussian blue, and composition changes in polyelectrochromic switching, J. Chem. Dalton Trans (1984) 2059 - 2061.  Ogura K., Nakayama M., Nakaoka K., Electrochemical quartz crystal microbalance and in situ infrared spectroscopic studies on the redox reaction of prussian blue, J. Electroanal. Chem. 474 (1999) 101 - 105.  Kulesza et al P.J, Electrochemical preparation and characterization of electrodes modified with mixed hexacyanoferrates of nickel and palladium, J. Electroanal. Chem 487 (2000) 57 -65.  Cui X., Hong L., Lin X., Electrochemical preparation, characterization and application of electrodes modified with hybrid hexacyanoferrates of copper and cobalt, J. Electroanal.Chem. 526 (2002) 115 - 124.  Fauci A.S., E. Braunwald, D.L. Kasper, S.L. Hauser, D.L. Longo, J.L. Jameson, J. Loscalzo, Harrison’s, principles of internal medicine, Mc-Graw Hills companies, (2008) 17th edn (Chapter 366)  Sivanesan A, Abraham S, John, Determination of l-dopa using electropolymerized 3,3′,3″,3″′ tetraaminophthalo cyanatonickel(II) film on glassy carbon electrode, Biosen Bioelectron 23 (2007) 708 – 713.  Bergamini M.F., Santos A.L., Stradiotto N.R, Zanoni M.V.B., A disposable electrochemical sensor for the rapid determination of levodopa, J. Pharm Biomed Anal 39 (2005) 54 - 59.  Kawde R.B., Laxmeshwar N.B., Santhanam K.S.V, A selective sensing of dopa in the presence of adrenaline, Sens Actuators B 23 (1995) 35 – 39.  Teixeira M.F.S, Marcolino-Junior L.H, Fatibello-Filho O., Dockal E.R, Bergamini M.F, An electrochemical sensor for L-dopa based on oxovana- dium-salen Thin film electrode applied flow injection system, Sens. Actuators B 122 (2006) 549 – 555.  Brown K.R, Walter D.G., Natan M.J., Seeding of colloidal Au nanoparticle solutions improved control of particle size and shape, Chem. Mater 12 (2000) 306 – 313.  Haiss W., Thanh N.T.K , Aveyard J., Fernig D.G., Determination of size and concentration of gold nanoparticles from uv-vis spectra, Anal. Chem 79 (2007) 4215 – 4221.  Torninaga M., Shimazoe T., Nagashima M., Kusuda H., Nkubo A., Kuwahara Y., Taniguchi I., Electro catalytic oxidation of dopamine at gold–silver alloy, silver and gold nanoparticles in an alkaline solution, J. Electroanal Chem 590 (2006) 37 – 46.
Fire Detection system plays an important role in surveillance and security systems. Fire detection systems are primarily designed to warn occupants of fire so that they may safely evacuate the premises. Correctly maintained and operating systems are effective and proven life saving devices. The available methods are based on mainly color and motion based methods, which detects fire using the color and motion features of fire. We can also use several classifiers to classify the fire pixels from non-fire pixels. The combination of several classifiers for the training process will give high performance. The system which uses the complementary information, based on color, shape variation, and motion analysis, will give better recognition compared to other methods.
Keywords : Fire detection, Multi-Expert Systems, motion based methods, color based methods.
 T. Celik, H. Demirel, H. Ozkaramanli, and M. Uyguroglu, “Fire detection using statistical color model in video sequences", J. Vis. Commun. Image Represent., vol. 18, no. 2, pp. 176185, Apr. 2007.  Y.-H. Kim, A. Kim, and H.-Y. Jeong, “RGB color model based the fire detection algorithm in video sequences on wireless sensor network", J. Distrib. Sensor Netw., vol. 2014, Apr. 2014, Art. ID 923609.  T. elik and H. Demirel, “Fire detection in video sequences using a generic color model", Fire Safety J., vol. 44, no. 2, pp. 147158, Feb. 2009.  T. elik, H. Ozkaramanli, and H. Demirel, “Fire pixel classification using fuzzy logic and statistical color model", in Proc. IEEE Int. Conf. Acoust., Speech Signal Process (ICASSP), vol. 1. Apr. 2007, pp. I-1205I-1208.  Y. Habiboglu, O. Gnay, and A. E. etin, “Covariance matrix-based fire and flame detection method in video", Mach. Vis. Appl., vol. 23, no. 6, pp. 11031113, Nov. 2012.  B. C. Ko, K.-H. Cheong, and J.-Y. Nam, “\Fire detection based on vision sensor and support vector machines", Fire Safety J., vol. 44, no. 3, pp. 322329, Apr. 2009.  C. Yu, Z. Mei, and X. Zhang, “A real-time video fire flame and smoke detection algorithm", Proc. Eng., vol. 62, pp. 891898, 2013.  X. Qi and J. Ebert, “A computer vision based method for fire detection in color videos", Int. J. Imag., vol. 2, no. S09, pp. 2234, 2009.  A. Rahman and M. Murshed, ”Detection of multiple dynamic textures using feature space mapping", IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 5, pp. 766771, May 2009.  B. U. Treyin, Y. Dedeoglu, U. Gdkbay, and A. E. etin, “Computer vision based method for real-time fire and flame detection", Pattern Recognit. Lett., vol. 27, no. 1, pp. 4958, Jan. 2006.  Pasquale Foggia, Alessia Saggese, and Mario Vento, “Real-Time Fire Detection for Video-Surveillance Applications Using a Combination of Experts Based on Color, Shape, and Motion", IEEE transactions on circuits and systems for video technology, vol. 25, No. 9, September 2015.
This paper presents a reversible data hiding method with contrast enhancement for medical images by preserving authenticity. Here the objective of reversible data hiding is to embed some secret information such as diagnosis report, patient ID etc., into the medical image in an invisible manner. In addition with the embedding of information into the image the proposed method achieves contrast enhancement without any visual distortions as in the previous methods. In addition with the contrast enhancement, the proposed method also provide security by introducing a visually meaningful image encryption so that instead of producing a noise like or texture like encrypted image this method will produce a visually meaningful encrypted image. Thereby it reduces the chance of security attacks. Also the embedding of digital watermark with this encryption will helps to ensure the authenticity of the medical images.
Keywords : Authentication, Background Segmentation, Encryption, Region of Interest, Reversible Data Hiding
 G. Coatrieux, H. Maitre, B. Sankur, Y. Rolland, R. Collorec, “Relevance of watermarking in medical images ", in: IEEE EMBS Int. Conf. Information Technology Applications in Biomedicine, 2000, pp. 250255.
 W. Pan, G. Coatrieux, J. Montagner, N. Cuppens, F. Cuppens, C. Roux, “Comparison of some reversible watermarking methods in application to medical images", in: 31st Annual Int. IEEE Conf. Engineering in Medicine and Biology Society, 2009, pp. 21722175.
 J. Tian, “Reversible data embedding using a difference expansion", IEEE Trans. Circ.Syst. Video Technol. 13 (8) (2003) 890896.
 Z. Ni, Y.Q. Shi, N. Ansari, W. Su, “Reversible data hiding", IEEE Trans. Circ. Syst.Video Technol. 16 (3) (2006) 354362.
 H.C. Huang, W.C. Fang, “Authenticity preservation with histogram-based reversible data hiding and quadtree concepts”, Sensors 11 (10) (2011) 97179731.
 H.T. Wu, J. Huang, “Reversible image watermarking on prediction error by efficient histogram modification", Signal Process. 92 (12) (2012) 30003009.
 H.C. Huang, F.C. Chang, “Hierarchy-based reversible data hiding", Expert Syst.Appl. 40 (1) (2013) 3443.
 B. Ou, X. Li, Y. Zhao, R. Ni, Y.-Q. Shi, “Pairwise prediction-error expansion for efficient reversible data hiding", IEEE Trans. Image Process. 22 (12) (2013) 50105021.
 X. Zhang, “Separable reversible data hiding in encrypted image", IEEE Trans. Inform. Forensics Secur. 7 (2) (2012) 826832.
 X. Wu, W. Sun, “High-capacity reversible data hiding in encrypted images by prediction error”, Signal Process. 104 (2014) 387400.35
 X. Liao, C. Shu, “Reversible data hiding in encrypted images based on absolute mean difference of multiple neighboring pixels of multiple neighboring pixels", J. Vis. Commun. Image Represent. 28 (4) (2015) 2127.
 H.T. Wu, J.L. Dugelay, Y.Q. Shi, “Reversible image data hiding with contrast enhancement", IEEE Signal Process. Lett. 22 (1) (2015) 8185.
 Hao-Tian Wua, Jiwu Huang, Yun-Qing Shi, “A reversible data hiding method with contrast enhancement for medical images", J. Vis. Commun. Image R. 31 (2015) 146153
 Otsu’s Method.