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SEABIRDS
      IEEE 2012 – 2013
   SOFTWARE PROJECTS IN
     VARIOUS DOMAINS
    | JAVA | J2ME | J2EE |
   DOTNET |MATLAB |NS2 |
SBGC                          SBGC

24/83, O Block, MMDA COLONY   4th FLOOR SURYA COMPLEX,

ARUMBAKKAM                    SINGARATHOPE BUS STOP,

CHENNAI-600106                OLD MADURAI ROAD, TRICHY- 620002




Web: www.ieeeproject.in
E-Mail: ieeeproject@hotmail.com
Trichy                        Chennai

Mobile:- 09003012150          Mobile:- 09944361169

Phone:- 0431-4012303
SBGC Provides IEEE 2012-2013 projects for all Final Year Students. We do assist the students
with Technical Guidance for two categories.

       Category 1 : Students with new project ideas / New or Old
       IEEE Papers.

       Category 2 : Students selecting from our project list.

When you register for a project we ensure that the project is implemented to your fullest
satisfaction and you have a thorough understanding of every aspect of the project.

SBGC PROVIDES YOU THE LATEST IEEE 2012 PROJECTS / IEEE 2013 PROJECTS

FOR FOLLOWING DEPARTMENT STUDENTS

B.E, B.TECH, M.TECH, M.E, DIPLOMA, MS, BSC, MSC, BCA, MCA, MBA, BBA, PHD,
B.E (ECE, EEE, E&I, ICE, MECH, PROD, CSE, IT, THERMAL, AUTOMOBILE,
MECATRONICS, ROBOTICS) B.TECH(ECE, MECATRONICS, E&I, EEE, MECH , CSE, IT,
ROBOTICS) M.TECH(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER
ELECTRONICS,        COMPUTER        SCIENCE,      SOFTWARE         ENGINEERING,       APPLIED
ELECTRONICS, VLSI Design) M.E(EMBEDDED                      SYSTEMS,       COMMUNICATION
SYSTEMS,         POWER          ELECTRONICS,         COMPUTER         SCIENCE,       SOFTWARE
ENGINEERING, APPLIED ELECTRONICS, VLSI Design) DIPLOMA (CE, EEE, E&I, ICE,
MECH,PROD, CSE, IT)

MBA(HR,       FINANCE,        MANAGEMENT,           HOTEL        MANAGEMENT,           SYSTEM
MANAGEMENT, PROJECT MANAGEMENT, HOSPITAL MANAGEMENT, SCHOOL
MANAGEMENT, MARKETING MANAGEMENT, SAFETY MANAGEMENT)

We also have training and project, R & D division to serve the students and make them job
oriented professionals
PROJECT SUPPORTS AND DELIVERABLES

 Project Abstract

 IEEE PAPER

 IEEE Reference Papers, Materials &

  Books in CD

 PPT / Review Material

 Project Report (All Diagrams & Screen

  shots)

 Working Procedures

 Algorithm Explanations

 Project Installation in Laptops

 Project Certificate
TECHNOLOGY         : JAVA

DOMAIN             : IEEE TRANSACTIONS ON IMAGE PROCESSING



S.No. IEEE TITLE     ABSTRACT                                                   IEEE
                                                                                YEAR
  1. A Primal–      Loss of information in a wavelet domain can occur 2012
     Dual Method    during storage or transmission when the images are
     for Total-     formatted and stored in terms of wavelet coefficients.
     Variation-     This calls for image inpainting in wavelet domains. In
     Based          this paper, a variational approach is used to formulate the
     Wavelet        reconstruction problem. We propose a simple but very
     Domain         efficient iterative scheme to calculate an optimal solution
     Inpainting     and prove its convergence. Numerical results are
                    presented to show the performance of the proposed
                    algorithm.
  2. A Secret-      A new blind authentication method based on the secret 2012
     Sharing-Based sharing technique with a data repair capability for
     Method for     grayscale document images via the use of the Portable
     Authentication Network Graphics (PNG) image is proposed. An
     of Grayscale   authentication signal is generated for each block of a
     Document       grayscale document image, which, together with the
     Images via the binarized block content, is transformed into several
     Use of the     shares using the Shamir secret sharing scheme. The
     PNG Image      involved parameters are carefully chosen so that as many
     With a Data    shares as possible are generated and embedded into an
     Repair         alpha channel plane. The alpha channel plane is then
     Capability     combined with the original grayscale image to form a
                    PNG image. During the embedding process, the
                    computed share values are mapped into a range of alpha
                    channel values near their maximum value of 255 to yield
                    a transparent stego-image with a disguise effect. In the
                    process of image authentication, an image block is
                    marked as tampered if the authentication signal
                    computed from the current block content does not match
                    that extracted from the shares embedded in the alpha
                    channel plane. Data repairing is then applied to each
                    tampered block by a reverse Shamir scheme after
                    collecting two shares from unmarked blocks. Measures
                    for protecting the security of the data hidden in the alpha
                    channel are also proposed. Good experimental results
                    prove the effectiveness of the proposed method for real
                    applications.
  3. Image          We investigate the problem of averaging values on 2012
     Reduction      lattices and, in particular, on discrete product lattices.
Using Means  This problem arises in image processing when several
   on Discrete  color values given in RGB, HSL, or another coding
   Product      scheme need to be combined. We show how the
   Lattices     arithmetic mean and the median can be constructed by
                minimizing appropriate penalties, and we discuss which
                of them coincide with the Cartesian product of the
                standard mean and the median. We apply these functions
                in image processing. We present three algorithms for
                color image reduction based on minimizing penalty
                functions on discrete product lattices.
4. Vehicle      We present an automatic vehicle detection system for 2012
   Detection in aerial surveillance in this paper. In this system, we
   Aerial       escape from the stereotype and existing frameworks of
   Surveillance vehicle detection in aerial surveillance, which are either
   Using        region based or sliding window based. We design a pixel
   Dynamic      wise classification method for vehicle detection. The
   Bayesian     novelty lies in the fact that, in spite of performing pixel
   Networks     wise classification, relations among neighboring pixels
                in a region are preserved in the feature extraction
                process. We consider features including vehicle colors
                and local features. For vehicle color extraction, we
                utilize a color transform to separate vehicle colors and
                non-vehicle colors effectively. For edge detection, we
                apply moment preserving to adjust the thresholds of the
                Canny edge detector automatically, which increases the
                adaptability and the accuracy for detection in various
                aerial images. Afterward, a dynamic Bayesian network
                (DBN) is constructed for the classification purpose. We
                convert regional local features into quantitative
                observations that can be referenced when applying pixel
                wise classification via DBN. Experiments were
                conducted on a wide variety of aerial videos. The results
                demonstrate flexibility and good generalization abilities
                of the proposed method on a challenging data set with
                aerial surveillance images taken at different heights and
                under different camera angles.
5. Abrupt       The robust tracking of abrupt motion is a challenging 2012
   Motion       task in computer vision due to its large motion
   Tracking Via uncertainty. While various particle filters and
   Intensively  conventional Markov-chain Monte Carlo (MCMC)
   Adaptive     methods have been proposed for visual tracking, these
   Markov-Chain methods often suffer from the well-known local-trap
   Monte Carlo  problem or from poor convergence rate. In this paper, we
   Sampling     propose a novel sampling-based tracking scheme for the
                abrupt motion problem in the Bayesian filtering
                framework. To effectively handle the local-trap problem,
we first introduce the stochastic approximation Monte
Carlo (SAMC) sampling method into the Bayesian filter
tracking framework, in which the filtering distribution is
adaptively estimated as the sampling proceeds, and thus,
a good approximation to the target distribution is
achieved. In addition, we propose a new MCMC sampler
with intensive adaptation to further improve the
sampling efficiency, which combines a density-grid-
based predictive model with the SAMC sampling, to
give a proposal adaptation scheme. The proposed method
is effective and computationally efficient in addressing
the abrupt motion problem. We compare our approach
with several alternative tracking algorithms, and
extensive experimental results are presented to
demonstrate the effectiveness and the efficiency of the
proposed method in dealing with various types of abrupt
motions.
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Java image processing ieee projects 2012 @ Seabirds ( Chennai, Bangalore, Hyderabad, Mumbai, Pune)

  • 1. SEABIRDS IEEE 2012 – 2013 SOFTWARE PROJECTS IN VARIOUS DOMAINS | JAVA | J2ME | J2EE | DOTNET |MATLAB |NS2 | SBGC SBGC 24/83, O Block, MMDA COLONY 4th FLOOR SURYA COMPLEX, ARUMBAKKAM SINGARATHOPE BUS STOP, CHENNAI-600106 OLD MADURAI ROAD, TRICHY- 620002 Web: www.ieeeproject.in E-Mail: [email protected] Trichy Chennai Mobile:- 09003012150 Mobile:- 09944361169 Phone:- 0431-4012303
  • 2. SBGC Provides IEEE 2012-2013 projects for all Final Year Students. We do assist the students with Technical Guidance for two categories. Category 1 : Students with new project ideas / New or Old IEEE Papers. Category 2 : Students selecting from our project list. When you register for a project we ensure that the project is implemented to your fullest satisfaction and you have a thorough understanding of every aspect of the project. SBGC PROVIDES YOU THE LATEST IEEE 2012 PROJECTS / IEEE 2013 PROJECTS FOR FOLLOWING DEPARTMENT STUDENTS B.E, B.TECH, M.TECH, M.E, DIPLOMA, MS, BSC, MSC, BCA, MCA, MBA, BBA, PHD, B.E (ECE, EEE, E&I, ICE, MECH, PROD, CSE, IT, THERMAL, AUTOMOBILE, MECATRONICS, ROBOTICS) B.TECH(ECE, MECATRONICS, E&I, EEE, MECH , CSE, IT, ROBOTICS) M.TECH(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS, COMPUTER SCIENCE, SOFTWARE ENGINEERING, APPLIED ELECTRONICS, VLSI Design) M.E(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWER ELECTRONICS, COMPUTER SCIENCE, SOFTWARE ENGINEERING, APPLIED ELECTRONICS, VLSI Design) DIPLOMA (CE, EEE, E&I, ICE, MECH,PROD, CSE, IT) MBA(HR, FINANCE, MANAGEMENT, HOTEL MANAGEMENT, SYSTEM MANAGEMENT, PROJECT MANAGEMENT, HOSPITAL MANAGEMENT, SCHOOL MANAGEMENT, MARKETING MANAGEMENT, SAFETY MANAGEMENT) We also have training and project, R & D division to serve the students and make them job oriented professionals
  • 3. PROJECT SUPPORTS AND DELIVERABLES  Project Abstract  IEEE PAPER  IEEE Reference Papers, Materials & Books in CD  PPT / Review Material  Project Report (All Diagrams & Screen shots)  Working Procedures  Algorithm Explanations  Project Installation in Laptops  Project Certificate
  • 4. TECHNOLOGY : JAVA DOMAIN : IEEE TRANSACTIONS ON IMAGE PROCESSING S.No. IEEE TITLE ABSTRACT IEEE YEAR 1. A Primal– Loss of information in a wavelet domain can occur 2012 Dual Method during storage or transmission when the images are for Total- formatted and stored in terms of wavelet coefficients. Variation- This calls for image inpainting in wavelet domains. In Based this paper, a variational approach is used to formulate the Wavelet reconstruction problem. We propose a simple but very Domain efficient iterative scheme to calculate an optimal solution Inpainting and prove its convergence. Numerical results are presented to show the performance of the proposed algorithm. 2. A Secret- A new blind authentication method based on the secret 2012 Sharing-Based sharing technique with a data repair capability for Method for grayscale document images via the use of the Portable Authentication Network Graphics (PNG) image is proposed. An of Grayscale authentication signal is generated for each block of a Document grayscale document image, which, together with the Images via the binarized block content, is transformed into several Use of the shares using the Shamir secret sharing scheme. The PNG Image involved parameters are carefully chosen so that as many With a Data shares as possible are generated and embedded into an Repair alpha channel plane. The alpha channel plane is then Capability combined with the original grayscale image to form a PNG image. During the embedding process, the computed share values are mapped into a range of alpha channel values near their maximum value of 255 to yield a transparent stego-image with a disguise effect. In the process of image authentication, an image block is marked as tampered if the authentication signal computed from the current block content does not match that extracted from the shares embedded in the alpha channel plane. Data repairing is then applied to each tampered block by a reverse Shamir scheme after collecting two shares from unmarked blocks. Measures for protecting the security of the data hidden in the alpha channel are also proposed. Good experimental results prove the effectiveness of the proposed method for real applications. 3. Image We investigate the problem of averaging values on 2012 Reduction lattices and, in particular, on discrete product lattices.
  • 5. Using Means This problem arises in image processing when several on Discrete color values given in RGB, HSL, or another coding Product scheme need to be combined. We show how the Lattices arithmetic mean and the median can be constructed by minimizing appropriate penalties, and we discuss which of them coincide with the Cartesian product of the standard mean and the median. We apply these functions in image processing. We present three algorithms for color image reduction based on minimizing penalty functions on discrete product lattices. 4. Vehicle We present an automatic vehicle detection system for 2012 Detection in aerial surveillance in this paper. In this system, we Aerial escape from the stereotype and existing frameworks of Surveillance vehicle detection in aerial surveillance, which are either Using region based or sliding window based. We design a pixel Dynamic wise classification method for vehicle detection. The Bayesian novelty lies in the fact that, in spite of performing pixel Networks wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and non-vehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixel wise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles. 5. Abrupt The robust tracking of abrupt motion is a challenging 2012 Motion task in computer vision due to its large motion Tracking Via uncertainty. While various particle filters and Intensively conventional Markov-chain Monte Carlo (MCMC) Adaptive methods have been proposed for visual tracking, these Markov-Chain methods often suffer from the well-known local-trap Monte Carlo problem or from poor convergence rate. In this paper, we Sampling propose a novel sampling-based tracking scheme for the abrupt motion problem in the Bayesian filtering framework. To effectively handle the local-trap problem,
  • 6. we first introduce the stochastic approximation Monte Carlo (SAMC) sampling method into the Bayesian filter tracking framework, in which the filtering distribution is adaptively estimated as the sampling proceeds, and thus, a good approximation to the target distribution is achieved. In addition, we propose a new MCMC sampler with intensive adaptation to further improve the sampling efficiency, which combines a density-grid- based predictive model with the SAMC sampling, to give a proposal adaptation scheme. The proposed method is effective and computationally efficient in addressing the abrupt motion problem. We compare our approach with several alternative tracking algorithms, and extensive experimental results are presented to demonstrate the effectiveness and the efficiency of the proposed method in dealing with various types of abrupt motions.