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


The linear algebra programming is very simple,so we move on to the matrix programming language as Simulation projects in Matlab. It work under the batch job as well as the interactive sessions.The sensor image can be measured based on the size of each photosite. The.The pixels provide photons,which converted to electric charges and the ones & zeroes.the numbers like any numbers that run via head which have  no physical size.the difficult task of image processing is segmentation of images.in the images,extract objects by segmentation.


Characteristics of simulation projects in Matlab:

  • Interactive environment are generated for problem solving,design and iterative exploration.
  • It is the great development tool for increase code quality, performance maximization, maintability using the programming interface.
  • Library for mathematical functions for statistics,fourier analysis ,filtering,linear algebra.
  • Ordinary differential equations,numerical integration,optimization for visualizing data &tools for custom plots.

The data with more information provide a small value for discrimination .the original measurements is inefficient in pattern recognition which obsure interpretation.

  • Redundant information:

In spectral data more information are repeated from image to image which complicates analysis  and unnecessarily classification.

  • Spatial vs spectral information:

The small portion of information content of more images represent gray values.

  • Information vs useful information:

Variability in image data is little or given classification problem with no value which declares the random or systematic variability as the target of interest or changes in the background targets not of immediate interest.

Content based images & video retrieval are the interested application in reduction methods.the feature vector with great dimensional generate problem in construction of data structures for retrieval & search.

Simulation projects in matlab using classification procedure:
  • Selection of feature.
  • The training stage.
  • Appropriate classification algorithm procedure.
  • Post classification smothering.
  • Accuracy assessment.

Optical character recognition (OCR) is a technology which allow user to transform variety of documents like PDF files,scanned paper documents,image captured by digital camera as searchable & editable data.

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