• Matlab
  • Simulink
  • NS3
  • OMNET++
  • NS2


The grouping of numerous built-in –commands.math functions,generating plots and numerical methods perforation are all done by matlab software.Matlab sample projects are used in large range of applications.

For Example

  • Control systems.
  • Computational finance.
  • Signal processing &communications.
  • Computational biology.
  • Image & video processing.
  • Test & measurement.


The quality of image can be improved using the big tool called digital image processing technique across various areas.Matlab sample projects with segmentation types are listed below:

Efficient graph – based segmentation
Hybrid segmentation algorithm
Mean shift segmentation

Efficient graph based segmentation:

  • Separability can be increased among background & foreground whole procedure speed up edge preserving property ,fast

Hybrid segmentation algorithm:

  • The region at what points growing process should be terminated over image segmentation or order resulting.

Mean shift segmentation:

  • The non parametric iterative algorithm or non parametric gradient density estimation by applying a kernel generalized approach

After completion of image segmentation, by edge detection the contour object are extracted,description of objects shape under the category of textures,shape ,object color can be determined.The technique of describing a group of features or characteristics image,which is the more efficient process or determine the useful information for classification and analysis.

The original values are modified so that most of the available range are used,which improve the contraction among background and targets called contrast enhancements.The most of the techniques of pattern recognition was not initially designed as permanent with more amount of inadequate features,under the feature selection problem there is a difficulty for learning algorithm for the selection of subset of features and removing the rest one.

Aspects of feature selection based on Matlab sample projects:

  • Understanding of data
  • Visualization of data facilitation
  • Requirement of storage
  • Training reduction
  • Prediction performance improvement

Among various application domains,the most important and challenging task is image classification which contains

  • Biometrics.
  • Robot navigation.
  • Biomedical imaging.
  • Remote sensing.
  • Vehicle navigation.

Finger print techniques with matlab sample projects are pattern matching and minutia based matching.pattern matching is the process of comparing two image to mark the similarities.

To identify duplicates pattern matching are applied in fingerprint systems.

In large area,widely used recognition technique is minutiae based matching which determine location direction of every point.

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