NCCT, MATLAB IEEE PROJECTS 2011 TITLES

NCCT, MATLAB IEEE PROJECTS 2011 TITLES

ncctchennai@gmail.com, 044-2823 5816, 98411 93224, 93801 02891

• A Basic Digital Watermarking Algorithm in Discrete Cosine transformation Domain
• A Comparison between a Neural Network and a SVM and Zernike Moments Based Blob Recognition Modules
• A Frequency Domain Multi-User Detector for TD-CDMA Systems
• A Messy Watermarking for Medical Image Authentication
• A More Secure Steganography Method in Spatial Domain
• A New Digital Image Scrambling Encryption Algorithm Based on Chaotic Sequence
• A Novel Method for using Adaptive Array Antennas in Ds-Cdma Mobile Radio Systems
• A Novel Method of Image Steganography in DWT Domain
• A Novel Robust Watermarking Algorithm Based On Two Levels DCT and Two Levels SVD
• A Novel Shape-based Diagnostic Approach for Early Diagnosis of Lung Nodules
• A Novel Trust Region Tracking Algorithm Based on Kernel Density Estimation
• A Simple and Fast Algorithm to Detect the Fovea Region in Fundus Retinal Image
• A Steganographic method based on Integer Wavelet Transform and Genetic Algorithm
• A Steganographic Method based on the JPEG Digital images
• Adaptive Image Watermarking Algorithm Based on Biorthogonal Wavelet Transform
• An Advanced Motion Detection Algorithm with Video Quality Analysis for Video Surveillance Systems

ncctchennai@gmail.com, 044-2823 5816, 98411 93224, 93801 02891, www.ncct.in  

• Boosting Color Feature Selection for Color Face Recognition
• Boosting Text Extraction From Biomedical Images using Text Region Detection
• Color Extended Visual Cryptography Using Error Diffusion
• Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Prediction Error
• Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement
• Efficient Relevance Feedback for Content-Based Image Retrieval by Mining User Navigation Patterns
• Encryption and Multiplexing of Fingerprints for Enhanced Security
• Enhanced Assessment of the Wound-Healing Process by Accurate Multiview Tissue Classification
• General framework of the construction of biorthogonal wavelets based on Bernstein bases
• Gradient Pro?le Prior and Its Applications in Image Super-Resolution and Enhancement
• Image based Secret Communication using Double Compression
• Image Fusion Method Based on NSCT and Robustness Analysis
• Image Preprocessing Methods in Face Recognition
• Image Segmentation Using Kernel Fuzzy C-Means Clustering on Level Set Method on Noisy Images
• Improved Red Blood Cell Counting in Thin Blood Smears
• Integrity Preservation and Privacy Protection for Medical Images with Histogram-Based Reversible Data Hiding

ncctchennai@gmail.com, 044-2823 5816, 98411 93224, 93801 02891, www.ncct.in   

• Key of Packaged Granary Grain Quantity Recognition — Grain Bags Image Processing
• Lung Cancer Detection by Using Artificial Neural Network and Fuzzy Clustering Methods
• Motion and Feature Based Person Tracking In Surveillance Videos
• Multiregion Image Segmentation by Parametric Kernel Graph Cuts
• Multi-resolution, multi-sensor image fusion general fusion framework
• Neural Network based Handwritten Character Recognition system without feature extraction
• Neural Networks for  the Detection and Localization of Breast Cancer
• Number Plate Recognition for Use in Different Countries Using an Improved Segmentation
• Online Voting System Powered By Biometric Security Using Steganography
• Parametrisation construction frame of lifting scheme
• Peak Power Analysis of MC-CDMA Employing Golay Complementary Sequences
• Reduced-Reference Image Quality Assessment Using Reorganized DCT-Based Image Representation
• Removal of High Density Salt and Pepper Noise Through Modi?ed Decision Based Unsymmetric Trimmed Median Filter
• Text Segmentation for MRC Document Compression
• The License Plate Recognition System Based on Fuzzy Theory and BP Neural Network

ncctchennai@gmail.com, 044-2823 5816, 98411 93224, 93801 02891, www.ncct.in   

• Wave(Let) Decide Choosy Pixel Embedding for stego
• Wavelet Enhanced Fusion Algorithm for Multisensor Images
• Transform Domain Progressive Image Decoding
• Desaturation of Digital Camera Images using chroma correlation
• Face Recognition using Gabor Filters and Local Binary Patterns
• Constant-brightness-plane based histogram equalization for color images
• Image Contrast enhancement using histogram specification
• Human Iris localization using modified ellipse fitting
• Image object segmentation and Region based Gamma mapping
• Support Vector Machine based retinal blood vessel detection and classification for eye disease detection
• Optic Disc detection using oriented line filter response for eye disease detection
• Image Segmentation and classification for Highway Traffic Symbol recogntion
• Wavelet domain Remote Sensing Satellite Image sharpening
• Forest Detection and Enhancement of Remote Sensing Satellite Images
• Combining Remote Sensing Satellite Images using Wavelet Planes
• Color Image restoration from high concentration impulse noise
• Lighting variation correction in Human Face Databases using Global and Local Face Features
• Illumination invariant Human face recognition using transform domain magnitude correction
• Robotic Scene Analysis based image enhancement
• Binary data hiding based Biometric Authentication System
• A highly secure steganographic scheme for medical and military images
• Image noise removal from random valued salt and pepper noise using directional filtering

ncctchennai@gmail.com, 044-2823 5816, 98411 93224, 93801 02891, www.ncct.in  

Matlab Projects @ NCCT, IEEE Projects Titles

Matlab Projects @ NCCT, IEEE Projects Titles

• A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features
• Intelligent Compression of Medical Images with Texture Information
• Satellite Image Enhancement using Image Modulation Function
• Randomization and Integer mapping based Lossless Watermarking of Images
• Selective blurring of Image content using Gaussian Model - Application to Film making
• Object Removal and Filling of Missing region in Images
• Digital Camera Image Enhancement using Alternating Projections
• A Low-Cost VLSI Implementation for Efficient Removal of Impulse Noise
• Blood Vessel Segmentation in Angiograms using Fuzzy Inference System and Mathematical Morphology
• Comparative Study of Image Segmentation Techniques and Object Matching using Segmentation
• Evaluation of Retinal Vessel Segmentation Methods for Microaneurysms Detection
• Image Retrieval from database using color quantization
• Background Detection and Image Enhancement of poorly Lighted images
• Medical Retinal blood vessel detection using gradient angle measurements for eye disease detection
• Transform Domain Color image enhancement using Discrete Cosine Transform
• Mean preserved Image Enhancment using Histogram Specification
• Blood vessel orientation based Optic Disc detection in medical retinal fundus images
• Two-Stage Hierarchical Image Segmentation using K-Means algorithm and Color Space Conversion
• Moving Object Segmentation in video sequences using Time-Frequency representation
• Genetic Algorithm based Image Noise Removal
• Exact Image Enhancement and Histogram processing using Wavelet Coefficients
• Lossless Color-Space Conversion of Images
• Image Quantization for segmentation using Partitioning Pixel Values
• Digital Image Processing Techniques for the Detection and Removal of Cracks in Digitized Paintings
• An SVD-based gray scale image quality measure for local and global assessment
• Enhancing Digital Cephalic Radiography With Mixture Models and Local Gamma Correction
• A closed-form approximation of the exact unbiased inverse of the Anscombe variance-stabilizing transformation
• Mixture of Gaussians-based Background Subtraction for Bayer-Pattern Image Sequences
• Removal of Artifacts from JPEG Compressed Document Images
• Scalable Face Image Retrieval with Identity-Based Quantization and Multi-Reference Re-ranking
• Screening of Diabetic Retinopathy - Automatic Segmentation of Optic Disc in Colour fundus Images
• X-Ray Image Categorization and Retrieval Using Patch-based Visual Words Representation

Matlab IEEE Projects Titles 2011

Matlab IEEE Projects Titles 2011 

• A Basic Digital Watermarking Algorithm in Discrete Cosine transformation Domain
• A Comparison between a Neural Network and a SVM and Zernike Moments Based Blob Recognition Modules
• A Frequency Domain Multi-User Detector for TD-CDMA Systems
• A Messy Watermarking for Medical Image Authentication
• A More Secure Steganography Method in Spatial Domain
• A New Digital Image Scrambling Encryption Algorithm Based on Chaotic Sequence
• A Novel Method for using Adaptive Array Antennas in Ds-Cdma Mobile Radio Systems
• A Novel Method of Image Steganography in DWT Domain
• A Novel Robust Watermarking Algorithm Based On Two Levels DCT and Two Levels SVD
• A Novel Shape-based Diagnostic Approach for Early Diagnosis of Lung Nodules
• A Novel Trust Region Tracking Algorithm Based on Kernel Density Estimation
• A Simple and Fast Algorithm to Detect the Fovea Region in Fundus Retinal Image
• A Steganographic method based on Integer Wavelet Transform and Genetic Algorithm
• A Steganographic Method based on the JPEG Digital images
• Adaptive Image Watermarking Algorithm Based on Biorthogonal Wavelet Transform
• An Advanced Motion Detection Algorithm with Video Quality Analysis for Video Surveillance Systems
• Boosting Color Feature Selection for Color Face Recognition
• Boosting Text Extraction From Biomedical Images using Text Region Detection
• Color Extended Visual Cryptography Using Error Diffusion
• Data Hiding in Motion Vectors of Compressed Video Based on Their Associated Prediction Error
• Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement
• Efficient Relevance Feedback for Content-Based Image Retrieval by Mining User Navigation Patterns
• Encryption and Multiplexing of Fingerprints for Enhanced Security
• Enhanced Assessment of the Wound-Healing Process by Accurate Multiview Tissue Classification
• General framework of the construction of biorthogonal wavelets based on Bernstein bases
• Gradient Pro?le Prior and Its Applications in Image Super-Resolution and Enhancement
• Image based Secret Communication using Double Compression
• Image Fusion Method Based on NSCT and Robustness Analysis
• Image Preprocessing Methods in Face Recognition
• Image Segmentation Using Kernel Fuzzy C-Means Clustering on Level Set Method on Noisy Images
• Improved Red Blood Cell Counting in Thin Blood Smears
• Integrity Preservation and Privacy Protection for Medical Images with Histogram-Based Reversible Data Hiding
• Key of Packaged Granary Grain Quantity Recognition — Grain Bags Image Processing
• Lung Cancer Detection by Using Artificial Neural Network and Fuzzy Clustering Methods
• Motion and Feature Based Person Tracking In Surveillance Videos
• Multiregion Image Segmentation by Parametric Kernel Graph Cuts
• Multi-resolution, multi-sensor image fusion general fusion framework
• Neural Network based Handwritten Character Recognition system without feature extraction
• Neural Networks for  the Detection and Localization of Breast Cancer
• Number Plate Recognition for Use in Different Countries Using an Improved Segmentation
• Online Voting System Powered By Biometric Security Using Steganography
• Parametrisation construction frame of lifting scheme
• Peak Power Analysis of MC-CDMA Employing Golay Complementary Sequences
• Reduced-Reference Image Quality Assessment Using Reorganized DCT-Based Image Representation
• Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter
• Text Segmentation for MRC Document Compression
• The License Plate Recognition System Based on Fuzzy Theory and BP Neural Network
• Wave(Let) Decide Choosy Pixel Embedding for stego
• Wavelet Enhanced Fusion Algorithm for Multisensor Images
• Transform Domain Progressive Image Decoding
• Desaturation of Digital Camera Images using chroma correlation
• Face Recognition using Gabor Filters and Local Binary Patterns
• Constant-brightness-plane based histogram equalization for color images
• Image Contrast enhancement using histogram specification
• Human Iris localization using modified ellipse fitting
• Image object segmentation and Region based Gamma mapping
• Support Vector Machine based retinal blood vessel detection and classification for eye disease detection
• Optic Disc detection using oriented line filter response for eye disease detection
• Image Segmentation and classification for Highway Traffic Symbol recogntion
• Wavelet domain Remote Sensing Satellite Image sharpening
• Forest Detection and Enhancement of Remote Sensing Satellite Images
• Combining Remote Sensing Satellite Images using Wavelet Planes
• Color Image restoration from high concentration impulse noise
• Lighting variation correction in Human Face Databases using Global and Local Face Features
• Illumination invariant Human face recognition using transform domain magnitude correction
• Robotic Scene Analysis based image enhancement
• Binary data hiding based Biometric Authentication System
• A highly secure steganographic scheme for medical and military images
• Image noise removal from random valued salt and pepper noise using directional filtering

Matlab FAQ - Interview Questions

Matlab FAQ - Interview Questions

WHAT IS MATLAB?

MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation.

Typical uses include:

 * Math and computation

 * Algorithm development

 * Modeling, simulation, and prototyping

 * Data analysis, exploration, and visualization

 * Scientific and engineering graphics

 * Application development, including Graphical User Interface building

WHAT ARE THE MATLAB SYSTEM PARTS?

The MATLAB system consists of five main parts:

 * The MATLAB language.

 * The MATLAB working environment.

 * Handle Graphics.

 * The MATLAB mathematical function library.

 * The MATLAB Application Program Interface (API).

EXPLAIN THE MATLAB LANGUAGE?

This is a high-level matrix/array language with control flow statements, functions, data structures, input/output, and object-oriented programming features. It allows both "programming in the small" to rapidly create quick and dirty throw-away programs, and "programming in the large" to create complete large and complex application programs.

EXPLAIN THE MATLAB WORKING ENVIRONMENT?

This is the set of tools and facilities that you work with as the MATLAB user or programmer. It includes facilities for managing the variables in your workspace and importing and exporting data. It also includes tools for developing, managing, debugging, and profiling M-files, MATLAB's applications.

EXPLAIN HANDLE GRAPHICS IN MATLAB?

This is the MATLAB graphics system. It includes high-level commands for two-dimensional and three-dimensional data visualization, image processing, animation, and presentation graphics. It also includes low-level commands that allow you to fully customize the appearance of graphics as well as to build complete Graphical User Interfaces on your MATLAB applications.

EXPLAIN THE MATLAB MATHEMATICAL FUNCTION LIBRARY?

This is a vast collection of computational algorithms ranging from elementary functions like sum, sine, cosine, and complex arithmetic, to more sophisticated functions like matrix inverse, matrix eigenvalues, Bessel functions, and fast Fourier transforms.

EXPLAIN THE MATLAB APPLICATION PROGRAM INTERFACE (API)?

This is a library that allows you to write C and Fortran programs that interact with MATLAB. It include facilities for calling routines from MATLAB (dynamic linking), calling MATLAB as a computational engine, and for reading and writing MAT-files.

HOW TO ADD NOISE TO AN IMAGE IN MATLAB?

The function noise.m, now installed on ashland too, adds Gaussian, uniform, salt and pepper, additive or multiplicative noise to an image.

WHAT CAN WE USE MATLAB FOR?

1. Simple calculations

2. Plotting and analyzing mathematical relationships (2D and 3D)

3. List & Matrix Operations

4. Writing script files (a type of programming)

5. Symbolic manipulation of equations

6. Advanced visualization, animation and GUI interface tools

VECTORIZATION WHAT IS THAT IN MATLAB? HOW TO DO IT?

Thinking is terms of full matrices/vectors and also some related functions for that * Use of filter(), which works beautifully for some time series models

ON WHAT MACHINES MATLAB SHOULD BE RUN?

We will run it from sthelens, and only if sthelens is down, from cher, orsay or tiree. It works on other machines too, but some of the other machines have older versions of the OS and core dump upon exiting from matlab. Some other local machines with new setups work fine. Try your local machine. Matlab is blocked from running on the servers

EXPLAIN LATEX IN MATLAB?

Matlab already handles naturally simple LaTeX encodings that allow introducing Greek lettters or modifying the font size and appearance in plots.

CAN WE RUN MATLAB WITHOUT GRAPHICS?

Sometimes you may want to run scripts which contain plotting commands without displaying the plots and without going into the script to comment out the commands. An example: if you're working from home and it's too slow to run graphics over the network. You can play a simple UNIX trick: % setenv DISPLAY /dev/null % matlab

HOW TO CORRECTLY APPLY THE GRAPHICS PATCHES IN MATLAB?

Open a LOCAL MACHINE window and type: xhost +ashland # Add the following code sequence just before the plot command that was giving you problems: figure; set(gcf,'renderer','zbuffer'); [s,w] = unix('echo $DISPLAY'); set(gcf,'XDisplay',w);

HOW TO CALL MATLAB IN BATCH MODE?

This can be done from the command line or from a makefile. You need a script (filename.m). Just type at the command line, or include in the makefile: matlab<filename.m where filename.m can write to disk a figure, a binary, an ascii file, anything you want.

EXPLAIN ABOUT STRESS ANALYSIS IN MATLAB?

People working on these areas as a aerospace engineers should have familiarity and exposure to NASTRAN and MATLAB with knowledge on space environment and modeling of flexible dynamics. These aerospace engineers will be responsible to conduct stress analysis on metallic and composite structures. NASTRAN, IDEAD, Oracle and PATRAN proficiency level is required. Their duties also include on aircraft which are metallic and composite structures. This includes and understanding of control surface stiffness and loop calculations, finite element modeling (FEM), fatigue testing requirement and analysis. 

Advantages of Matlab

Advantages of Matlab

• Huge Linear Algebra and Numerical Algorithms
• Easy to Learn Script Language
• Suitable for Fast Mock up GUI and Prototyping
• Possibly to Integration C Functions
• Lots of Free Extensions for Any Needs
• Very Powerful Language
• Name Conventions are Great
• Can be used to Presentation because GUI is look like Notepad
• Very Good Visualization Library
• Facilitates Rapid Testing and Prototyping where Necessary

What Is Simulink?

What Is Simulink?

Simulink is an interactive environment for modeling, simulating, and analyzing dynamic, multidomain systems. It lets you build a block diagram, simulate the system’s behavior, evaluate its performance, and refine the design. Simulink integrates seamlessly with MATLAB, providing you with immediate access to an extensive range of analysis and design tools. These benefits make Simulink the tool of choice for control system design, DSP design, communications system design, and other simulation applications.

Blocksets are collections of application-specific blocks that support multiple design areas, including electrical power-system modeling, digital signal processing, fixed-point algorithm development, and more. These blocks can be incorporated directly into your Simulink models.

Real-Time Workshop® is a program that generates optimized, portable, and customizable ANSI C code from Simulink models. Generated code can run on PC hardware, DSPs, microcontrollers on bare-board environments, and with commercial or proprietary real-time operating systems

The MATLAB System

The MATLAB System

The MATLAB system consists of five main parts:

Development Environment. This is the set of tools and facilities that help you use MATLAB functions and files. Many of these tools are graphical user interfaces. It includes the MATLAB desktop and Command Window, a command history, an editor and debugger, and browsers for viewing help, the workspace, files, and the search path.

The MATLAB Mathematical Function Library. This is a vast collection of computational algorithms ranging from elementary functions, like sum, sine, cosine, and complex arithmetic, to more sophisticated  functions like matrix inverse, matrix eigenvalues, Bessel functions, and fast Fourier transforms.

The MATLAB Language. This is a high-level matrix/array language with control flow statements, functions, data structures, input/output, and object-oriented programming features. It allows both “programming in the small” to rapidly create quick and dirty throw-away programs, and “programming in the large” to create large and complex application programs.

Graphics. MATLAB has extensive facilities for displaying vectors and matrices as graphs, as well as annotating and printing these graphs. It includes high-level functions for two-dimensional and three-dimensional data visualization, image processing, animation, and presentation graphics. It also includes low-level functions that allow you to fully customize the appearance of graphics as well as to build complete graphical user interfaces on your MATLAB applications.

The MATLAB Application Program Interface (API). This is a library that allows you to write C and Fortran programs that interact with MATLAB. It includes facilities for calling routines from MATLAB (dynamic linking), calling MATLAB as a computational engine, and for reading and writing MAT-files