International Journal of Innovative Science and Modern Engineering(TM)
Exploring Innovation| ISSN:2319–6386(Online)| Reg. No.:68121/BPL/CE/12| Published by BEIESP| Impact Factor:3.86
Home
Articles
Conferences
Editors
Scopes
Author Guidelines
Publication Fee
Privacy Policy
Associated Journals
Frequently Asked Questions
Contact Us
Volume-2 Issue-1: Published on December 15, 2013
34
Volume-2 Issue-1: Published on December 15, 2013

  Download Abstract Book

S. No

Volume-2 Issue-1, December 2013, ISSN: 2319–6386 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Reshma S. K, I. Raghavendar

Paper Title:

Hybrid Wind Solar Sources at Distribution Level Using New Control Method for Power Quality Improvement

Abstract: Electric utilities and end users of electric power are becoming increasingly concerned about meeting the growing energy demand. Seventy five percent of total global energy demand is supplied by the burning of fossil fuels. But increasing air pollution, global warming concerns diminishing fossil fuels and their increasing cost have made it necessary to look towards renewable sources as a future energy solution. Since the past decade, there has been an enormous interest in many countries on renewable energy for power generation. This paper has presented a novel control of an existing grid interfacing inverter to improve the power quality at point of common coupling for a 3-phase 4-wire distributed generation system. The inverter is controlled to perform multifunction device by incorporating active power filter functionality. The grid interfacing inverter can be effectively used to compensate the load reactive power, current unbalance and harmonic distortions in addition to active power injection from renewable energy sources. This enables the grid to supply/receive sinusoidal and balanced power at unity power factor. All these functions may be accomplished either individually or simultaneously. This new method is demonstrated with extensive MATLAB/simulink.

Keywords:
Distribution generation (DG), Power quality (PQ), Renewable energy source (RES), Point of common coupling (PCC), Hysteresis Band (HB).


References:

1.        J. P. Pinto, R. Pregitzer, L. F. C. Monteiro, and J. L. Afonso, “3-phase 4-wire shunt active power filter with renewable energy interface,” Presented at the Conf. IEEE Renewable Energy & Power Quality, Seville, Spain, 2007.
2.        Murat Kale, Engin Ozdemir “An adaptive hysteresis band current controller for shunt active power filter” Electric Power System Research 73(2005) 113-119

3.        F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, “Overview of control and grid synchronization for distributed power generation systems,” IEEE Trans. Ind. Electron., vol. 53, no. 5, pp. 1398–1409,Oct. 2006.

4.        J. M. Carrasco, L. G. Franquelo, J. T. Bialasiewicz, E. Galván, R. C. P. Guisado, M. Á. M. Prats, J. I. León, and N. M. Alfonso, “Power electronic systems for the grid integration of renewable energy sources: A survey,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1002–1016,Aug. 2006.

5.        RVD  Rama  Rao and  Dr.subhransu.sekhar.Dash “power quality enhancement by unified power quality conditioner using ANN with hysteresis control.”International journal of computer applications (0975 - 8887) volume6No.1, September 2010.

6.        Luis A.  Moran, Juan  W.Dixon, Jose R.Espinoza, Rogel R. Wallace “Using Active Power Filters To Improve Power Quality.”Departmento de Ing.Electrica Universidad de concepcion-Chile, Departamento de Ing. Electrica Universidad catolica de dhile santigo-chile.

7.        Suresh  Mikkili  and  Anup  Kumar  Panda “PI and Fuzzy logic controller based 3-phase 4-wire Shunt Active Filters for the Mitigation of current Harmonics with the Id-Iq Control Strategy”, journal of Power electronics,vol. 11,No. 6,November 2011.


1-6

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

2.

Authors:

Tariq Ali, Nouman Iqbal,   Md. Zeeshan, Md. Zulfiqar Ali Khan

Paper Title:

Evaluation of the Compressive Strength of Concrete for Partial Replacement of Over Burnt Brick Ballast Aggregate

Abstract: Regional conditions enforced engineers to generate a study on concrete which incorporate Over Burnt Brick Ballast Aggregate partially due to their abundance. 5%, 10%, 15%, and 20% (M05, M10, M15, M20) incorporation was used as partial replacement of natural coarse aggregate in concrete. Analysis of incorporated concrete was done in fresh state as well in hardened state to evaluate different properties of concrete i.e. slump, compaction factor test, unit weight, and compressive strength are evaluated. From all the results and  experimental approach it is concluded that Concrete formed with over burnt brick ballast aggregate showed beneficial performance as compared with the concrete made up of natural aggregate obtained from local resources. The over burnt brick ballast aggregate showed 14.75% increase in Compressive strength for 20% replacement. It reduces the cost of concrete by reducing the aggregate cost and produces economical infrastructure system.

Keywords:
Over Burnt brick Ballast Aggregate, Kiln, Compressive strength

References:

1.        Marek, C. R. Gallaway, B. M. and Long, R. E., “Look at Processed Rubble – It is a Valuable Source for Aggregates”, Roads and Streets, Vol. 114, No. 9, Sept. 1971, p 82-85.
2.        Barra, M and Vazquez, E, “Properties of Concrete with Recycled Aggregates : Influence of the Properties of the Aggregates and Their Interpretation”, Proceedings of the International Symposium organized by the Concrete Technology Unit, London, 1998

3.        Ghosh, S. N., “Progress in Cement and Concrete”, Science & Technology, Thomas Telford, Pt. I, Vol. I, 1992

4.        Rao, Akash; K.N Jha, and Sudhir Misra; “A framework for use of construction and demolition waste as recycled aggregate in India”, The Indian Concrete Journal, January, 2006.


7-10

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

3.

Authors:

S. R. Patil, Raveena Chavan, Anjali Shinde, T. Jecintha Joy, Nirmala Wakale

Paper Title:

Intelligent Cooking Providing Automatic Time and Temperature Setting Using Image Processing With Wide Range of Recipes for Microwave Ovens

Abstract: In this, accurate automatic cooking is done using Image Processing. Automatic cooking means time and temperature will be set automatically at fly time. It involves comparing images of cooked food and food currently being cooked. No need to decide the preset timing. This software can be used in microwaves and ovens. Component detection algorithms and Image processing algorithms will be used. Input and output will be images like photographs or frames of video. Images will be treated as 2D signals and signal processing techniques will be applied. Both hardware and software components will be used. Feedback from oven can be taken into a webcam and videos will be converted into frames of images at runtime. Here we are certain about the exact image which will be our input. This is the main advantage over fuzzy logic where in we get approximate input rather than an exact input. It is effective in time and speed. It is efficient and user friendly. We will have a wide number of recipes in our database.

Keywords:
Automatic Time and Temperature Setting, Image Processing, Intelligent Cooking, Microwave Ovens.


References:

1.        Jinghao Fei, Jie Yang, Jianping Fan, “TOWARDS VIRTUALLY COOKING CHINESE FOOD” School of Computer Science, Carnegie Mellon University, PA 15213 USA; Shenzhen Institute of Advanced Technology (SIAT), 518054 China; Institute of Computing Technology (ICT), Chinese Academy of Sciences, 100190 China(2009).
2.        Sheng-Yu Peng, Kanoksak Wattanachote, Hwei-Jen Lin, Kuan-Ching Li, “A Real-Time Hand Gesture Recognition System for Daily Information Retrieval from Internet” CSIE, Tamkang University Taiwan Wattanachote; CSIE, Asia University Taiwan CSIE, Tamkang University Taiwan CSIE, Providence University Taiwan(2011).

3.        Daniel R. Schlegel, Albert Y. C. Chen, Caiming Xiong, Jeffrey A. Delmerico, Jason J. Corso, “AirTouch: InteractingWith Computer Systems At A Distance” , Dept. of Computer Science and Engineering,SUNY at Buffalo(2010).

4.        Helly Patel,  Mahesh P. Wankhade,“ HUMAN TRACKING IN VIDEO SURVEILLANCE”, Department of Computer Engineering, Zeal Education Society’s Dnyanganga College of Engineering and Research,Pune, Maharastra, India ; Department of Computer Engineering, Sinhgad College of Engineering, Pune, Maharashtra, India. (December 2011).

5.        J. Jeedella and H. Al-Ahmad , “AN ALGORITHM FOR WATERMARKING MOBILE PHONE COLOUR IMAGES USING BCH CODE”, Khalifa University of Science, Technology & Research,P.O. Box 573, Sharjah, UAE. (February 19-22,2011).

6.        Bingbing Ni, Zheng Song, and Shuicheng Yan ,  “Web Image and Video Mining Towards Universal and Robust Age Estimator” , Senior Member, IEEE. (Volume 3, Issue 1, 2012).              

7.        Bingbing Ni, Zheng Song, and Shuicheng Yan, “Web Image and Video Mining Towards Universal and Robust Age Estimator”,  Senior Member, IEEE (VOL. 13, NO. 6, DECEMBER 2011).

8.        Gonzalez, Rafael C. & Woods, Richard E., “Thresholding” , In Digital Image Processing, pp. 595–611. Pearson Education. ISBN 81-7808-629-8. (2002).

9.        Modi, C.K.; Jain, K.R.,“QUALITY EVALUATION OF HYDROTHERMAL TREATED QUICKER COOKING SCENTED RICE BY QUANTIFICATION OF QUICKNESS OF COOKING TIME AND MECHANICAL STRENGTH USING MACHINE VISION”, Computational Intelligence and Communication Networks (CICN), 2011 International Conference on. (vol., no., pp.639,643, 7-9 Oct. 2011).

10.     Akagi, Y.; Aoki, Y.; Hoshikawa, E.; Sakashita, T., "Detection of professional techniques in cooking by image processing", SICE, 2007 Annual Conference .( vol., no., pp.1484,1488, 17-20 Sept. 2007).


11-16

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

4.

Authors:

P. Sreenivasa Rao, M. Janani, P. Chenna Reddy

Paper Title:

TFRC for Congestion Control in Wireless Environment

Abstract: Real Time Applications (RTAs) have stringent requirements. Congestion in the network results in packet loss, delay and reduction in throughput which are not tolerable by RTAs. Proper congestion control mechanisms are necessary for RTAs. TCP provides congestion control mechanisms. But it is a protocol which is designed for wired networks. TCP treats packet loss as an indication of congestion which is not true in wireless networks. In wireless networks packets may be lost due to various other reasons. UDP has no congestion control mechanisms and is not good for the stability of the Internet. TCP Friendly Rate Control (TFRC) protocol is designed by Internet Engineering Task Force (IETF) especially for RTAs. This paper studies the performance of TFRC, TCP and UDP in wireless environment.

Keywords:
Real Time Applications, TFRC, TCP, UDP.


References:

1.        J. Postel, "Transmission Control Protocol", RFC-793, September 1981.
2.        Handley, Floyd, Widmer and Padhye, “TCP-Friendly Rate Control (TFRC): Protocol Specification”, IETF RFC 5348, April 2008.

3.        S. Floyd, J. Padhye, and E. Kohler, “Profile for Datagram Congestion Control Protocol (DCCP) Congestion Control ID 3: TCP-Friendly Rate Control (TFRC)”, IETF RFC 4342, March 2006.

4.        Bin Zhou, Cheng Peng Fu, Victor 0. K. Li, “TFRC Veno: An Enhancement of TCP Friendly Rate Control over Wired/Wireless Networks”, IEEE International Conference on Network Protocols, Beijing, China, 16-19 October 2007.

5.        Christos Bouras, Vassilis Papapanagiotou, Kostas Stamos, Giannis Zaoudis, “The TFRC protocol and its usage for wireless video transmission”, In proceeding of: Software, Telecommunications & Computer Networks, October 2009.  

6.        The VINT Project, “The ns Manual (formerly ns notes and documentation)”, http://www.isi.edu/nsnam/ns/ns-documentation. html, November 2011.

17-20

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

5.

Authors:

P. B. Selvapriya

Paper Title:

Different Software Testing Strategies and Techniques

Abstract: In this paper main testing strategies and techniques are precisely described. General classification is outlined: two testing methods – black box testing and white box testing, and their often used techniques: Black Box techniques: Equivalent Partitioning, Cause-Effect Graphing Techniques, Boundary Value Analysis and Comparison Testing. White Box techniques: Loop Testing, Basis Path Testing, and Control Structure Testing.

Keywords:
Black box testing and white box testing, and their often used techniques.


References:

1.        http://www.his.sunderland.ac.uk/~cs0mel/comm83wk5. doc, February 08, 2009.
2.        Stacey, D. A., “Software Testing Techniques”
3.        Guide to the Software Engineering Body of Knowledge, Swebok – A project of the IEEE Computer Society Professional Practices Committee, 2004.
4.        “Software Engineering: A Practitioner’s Approach, 6/e; Chapter 14: Software Testing Techniques”, R.S. Pressman & Associates, Inc., 2005.
5.        Myers, Glenford J., IBM Systems Research Institute, Lecturer in Computer Science, Polytechnic Institute of New York, “The Art of Software Testing”, Copyright 1979. by John Wiley & Sons, Inc.
6.        Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/wiki/
7.        http://www2.umassd.edu/CISW3/coursepages/pages/CI S311/outline.html
8.        Wei–Tek, Tsai, “Risk – based testing”, Arizona State University, Tempe, AZ 85287
9.        Redmill, Felix, “Theory and Practice of Risk-based Testing”, Software Testing, Verification and Reliability, Vol. 15, No. 1, March 2005.
10.     http://www.testingstandards.co.uk/living_glossary.htm# Testing, February 08, 2009.
11.     http://www.pcmag.com/encyclopedia_term/0,2542,t=b lack+box+testing&i=38733,00.asp, February 08, 2009.
12.     http://www.pcmag.com/encyclopedia_term/0,254 2,t=gray+box+testing&i=57517,00.asp, February 08, 2009.
13.     “Software Testing Methods and Techniques”

21-24

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

6.

Authors:

Anjumara Inamdar, Heena Aggarwal, Sayali Kadam, Mayuri Kadhane

Paper Title:

COMPDROID - Remote Desktop Access through Android Mobile Phone

Abstract: In this paper we will enlist the process to access the remote desktop through android mobile phone. This will be done through networking. User can access the desktop and manipulate the desktop, capture the screen, zooming and panning, transfer the files through any part of world due to network connection irrespective of various platforms like windows, linux, mac. For this purpose the COMPDROID developed by us will be installed on user’s Android mobile phone and servlets are invoked on server side i.e. remote desktop. We are also providing application shortcuts for those applications which are frequently used.

Keywords:
Android, Mobile, Desktop, Internet, Networking, Servlets.


References:

1.        Archana Jadhav, "VNC ARCHITECTURE BASED REMOTE DESKTOP ACCESS   THROUGH ANDROID MOBILE PHONES", International Journal of Advanced Research in Computer and Communication Engineering   Vol. 1, Issue 2, April 2012
2.        Vipul Delwadia , Stuart Marshall , Ian Welch "USING REMOTELY EXECUTING SOFTWARE VIA A MOBILE DEVICE"

3.        Buntarou Shizuki, "VNC-BASED ACCESS TO REMOTE COMPUTERS FROM CELLULAR PHONES"

4.        Timothy Vidas ,"ALL YOUR DROID ARE BELONG TO US: A SURVEY OF CURRENT ANDROID ATTACKS"

5.        Chaitali Navasare, Deepa Nagdev and Jai Shree, "POCKETDROID - A PC REMOTE CONTROL", 2012 International Conference on Information and Network Technology (ICINT 2012) IPCSIT vol. 37 (2012)

6.        R.Manikandasamy , "REMOTE DESKTOP CONNECTION USING MOBILE PHONE", International Journal of Science, Engineering and Technology Research (IJSETR) Volume 2, Issue 8, August 2013

7.        Ajit Kotkar and Alok Nalawade, "ANDROID BASED REMOTE DESKTOP CLIENT",  International Journal of Innovative  Research in Computer and Communication Engineering  Vol. 1, Issue 2, April 2013

8.         Sonam Gavhane , "REMOTE DESKTOP ON MOBILE" , International Journal of Innovations in Engineering and Technology (IJIET)

9.        K.S. Kuppusamy, "A MODEL FOR REMOTE ACCESS AND PROTECTION OF SMARTPHONES USING SHORT MESSAGE SERVICE", International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.1, February 2012

10.     Dhananjay .A.Sherigar ,"3 FACTOR AUTHENTICATION FOR REMOTE ACCESSING USING ANDROID DEVICE ", International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 2, February- 2013 ISSN: 2278-0181


25-27

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

7.

Authors:

Bader Abdo Hakami

Paper Title:

Environmental Issues at the Global Level: Causes and Strategies to Control

Abstract: This research study aims at underlying the various global environmental issues and the factors that lead to those issues on the planet. The global environment is affected by the various activities and conditions of different countries of the world like increasing industrial practices, population, etc. and these activities adversely affects the natural resources of the global environment like land, fossil fuels, etc. Two major causes were reported against the environment and they were global warming and energy crisis. The global issues related to the environment occurred due to the excessive emission of the green house gases. The green house gases are the harmful gases that results in the increasing surface temperature of the earth and thus resulting in the global warming. The carbon dioxide, methane and nitrous oxide are some of the green house gases out of which the methane is the most powerful whereas the carbon dioxide s maximum emitted by the human activities.

Keywords:
Global environmental issues, global warming, biodiversity, greenhouse gases, climate change, and animal agriculture. 

References:

1.        Anand, S.V. (2013). Global Environmental Issues. Open Access Scientific Reports, 2 (2), pp 1-9.
2.        Bisgrove, R. and Hadley, P. (2002). Gardening in the global greenhouse: the impacts of climate change on gardens in the UK. UKCIP, Oxford, UK.

3.        Cassar, M. (2005). Climate Change and the Historic Environment. Centre for Sustainable Heritage, University College London, London, UK.

4.        Cranfield, S. (2001). UK: United Kingdom Climate Impacts Programme, Department of the Environment, Food and Rural Affairs and United Kingdom Water Industries Research.

5.        Epstein, P.R. (2002). Is Global Warming Harmful to Health? South American Magazine.

6.        Hansen, J. E. (2001). “The Global Warming Debate”, NASA Goddard Institute for Space Studies Education, http://www.giss.nasa.gov/edu/gwdebate/.

7.        Harrabin, R. (2007). How climate change hits India's poor. BBC News.

8.        Holman, I., Loveland, P.J., Nicholls, R.J., Shackley, S., and Berry, P.M. (2001). REGIS - Regional climate change impact and response studies in East Anglia and in North West England (RegIS). DEFRA, UK Climate Impacts Programme, UK.

9.        Hulme, M., Jenkins, G.J., Lu, X., Turnpenny, J.R., and Mitchell, T.D. (2002). Climate change scenarios for the United Kingdom: the UKCIP02 Scientific Report. Open Grey: 119.

10.     Karanth, K.P. (2006). Out-of-India Gondwanan origin of some tropical Asian biota. Current Science WWF International Organization 6: 1-4.

11.     McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J., and White, K.S. (2001). A Report on Working Group II: Intergovernmental Panel on Climate Change. Summary for Policymakers, IPCC: 1-18.


28-32

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html

8.

Authors:

Thippeswamy G, Ambika G. N,  Vidya R

Paper Title:

Algorithms and Techniques used for 3D Face Recognition in the Presence of Expressions and Occlusion

Abstract: The purpose of this study is to enhance the algorithms towards the development of an efficient three dimensional face recognition system in the presence of expressions as well as for occluded face. The overall aim is to analyze patterns of expressions based on techniques relating to feature distances and also to segment the human face into non-occluded and occluded part of the occluded human face image. Here we are using two steps the first step is to recognize the face in different patterns of expressions and the second step is recognizing the occluded face. The first process can be obtained by using Euclidean distances, geodesic distances and regression models.  And the second process is obtained by using Mean Based Weight Matrix (MBWM) algorithm.

Keywords:
Face Recognition; Feature Distances; Expressions; Regression Analysis, MBWM, support vector machine, SLBM, occlusion, LBP.


References:

1.        Y. Wang, C. Chua and Y. Ho, “Facial Appearance Detection and Face Recognition from 2D and 3D Images,” Pattern Recognition Letters, Vol. 23, No. 10, 2001, pp. 1191-1202. doi:10.1016/S0167-8655(02)00066-1
2.        X. Han, H. Ugail and I. Palmer, “Method of Characteris-ing 3D Faces Using Gaussian Curvature,” Chinese Con-ference on Pattern Recognition, Nanjing, 4-6 November 2009, pp. 528-532.

3.        B. Amberg, R. Knothe and T. Vetter, “Expression Invariant 3D Face Recognition with a Morphable Model,” IEEE International Conference on Automatic Face and Gesture Recognition, 2008, pp. 1-6. doi:10.1109/AFGR.2008.4813376

4.        N. Alyuz, B. Gokberk, H. Dibeklioglu and L. Akarun, “Component-Based Registration with Curvature Descriptors for Expression Insensitive 3D Face Recognition,” IEEE In- ternational Conference on Automatic Face & Gesture Rec- ognition, Amsterdam, 17-19 September 2008, pp. 1-6.

5.        D. Smeets, T. Fabry, J. Hermans, D. Vandermeulen and P. Suetens, “Fusion of an Isometric Deformation Modeling Approach Using Spectral Decomposition and a Region- Based Approach Using ICP for Expression-Invariant 3D Face Recognition,” The 20th International Conference on Pattern Recognition, Istanbul, 23-26 August 2010, pp. 1172-1175. doi:10.1109/ICPR.2010.293

6.        Y. Wang, G. Pan and Z. Wu, “3D Face Recognition in the Presence of Expression: A Guidance-Based Constraint Deformation Approach,” IEEE Conference on Computer Vision and Pattern Recognition, 2007, pp. 1180-1187. doi:10.1109/CVPR.2007.383277

7.        X. Lu and A. K. Jain, “Deformation Modeling for Robust 3D Face Matching,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, 2006, pp. 1377-1383. doi:10.1109/CVPR.2006.96

8.        I. A. Kakadiaris, G. Passalis, G. Toderici, M. N. Murtuza, Y. Lu, N. Karampatziakis and T. Theoharis, “Three-Di- mensional Face Recognition in the Presence of Facial Ex-pressions: An Annotated Deformable Model Approach,” IEEE Transactions on Pattern Analysis and Machine Intel- ligence, Vol. 29, No. 4, 2007, pp. 640-649. doi:10.1109/TPAMI.2007.1017

9.        H. Lee and D. Kim, “Expression-Invariant Face Recognition by Facial Expression Transformations,” Pattern Recognition Letters, Vol. 29, No. 13, 2008, pp. 1797-1805. doi:10.1016/j.patrec.2008.05.012

10.     F. R. Al-Osaimi, M. Bennamoun and A. Mian, “On De- composing an Unseen 3D Face into Neutral Face and Ex- pression Deformations,” Advances in Biometrics, Vol. 5558, 2009, pp. 22-31. doi:10.1007/978-3-642-01793-33

11.     Priya, G.N. and R.S.D.W. Banu, 2012. A Simplified Local Binary Mean (SLBM) based human gender classification. Eur. J. Sci. Res., 71: 435-442.

12.     Shang, L., C. Zhou, Y. Gu and Y. Zhang, 2010. Face recognition using the feature fusion technique based on LNMF and NNSC algorithms. Adv.

13.     Intell. Computer. Theories Appli., 6215: 547-554. DOI: 10.1007/978-3-642-14922-1_68 Wright, J., A. Ganesh, A. Yang, S.S. Sastry and Y.

14.     Ma, 2009. Robust face recognition via sparse representation. IEEE Trans. Patt. Anal. Mach. Intell., 31: 210-227. DOI: 10.1109/TPAMI.2008.79

15.     Zhang, W., S. Shan, W. Gao, X. Chen and H. Zhang, 2005. Local Gabor Binary Pattern Histogram Sequence (LGBPHS): A novel non-statistical model for face representation and recognition. Proceedings of the 10th IEEE Conference Computer Vision, Oct. 17-21, IEEE Xplore Press, China, pp: 786-791. DOI: 10.1109/ICCV.2005.147

16.     Zhang, W., S. Shan, X. Chen and W. Gao, 2007. Local gabor binary patterns based on kullback–leibler divergence for partially occluded face recognition. IEEE Signal Proc. Lett., 14: 875-878. DOI 10.1109/LSP.2007.903260

17.     X. Chai, S. Shan, X. Chen and W. Gao, “Locally Linear Regression for Pose-Invariant Face Recognition,” IEEE Transactions on Image Processing, Vol. 16, No. 7, 2007, pp. 1716-1725. doi:10.1109/TIP.2007.899195

18.     I. Naseem, R. Togneri and M. Bennamoun, “Linear Regression for Face Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 11, 2010, pp. 2106-2112. doi:10.1109/TPAMI.2010.128


33-38

www.blueeyesintelligence.org/attachments/File/fee/2checkout_download.html