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


In the  field of technical computing ,the one of the high- performance language is MATLAB. MATLAB Related projects involves the process of visualization, programming environment and computation.DIP projects are mostly done under MATLAB. The particular image consist of many objects then each object include several regions related to different parts of segmentation object which is the method of dividing an image as regions.


Aspects of feature extraction with matlab related projects:

  • Feature construction.
  • Sudset generation feature.
  • Definition of evaluation criterion.
  • Estimation of evaluation criterion.

The important details of image (or) objects by machine (or) man can be easily detected using image enhancement operators.

Uneven Distributed gray values contained in most images. The common thing is to determine the image with all the intensity values lie inside a small range.

The quality of image is purely enhanced by histogram modification, It is used when the image is viewed by human observer. The common function of histogram is normalization which contain image  histogram as flat as possible way. The addition of all components normalized histogram is 1.

The method of pattern recognition performance can be increased by removing  an intra-class variability from the sampled data by different feature processing techniques.

The technique of image classification is done by applying classifiers to image declarations received from the pooling step.

Matlab Related Projects with Classification Techniques:

  • Object based image analysis.
  • Unsupervised image classification.

The  images are declaredby the smaller unit called pixel. The reflectance statistics for  particular pixels can be applied in image classification.

Classification methods:

  • Supervised Image classification.
  • Unsupervised Image classification.

The study of how machines can focus the environment and learn to split patterns of interest called pattern recognition. The well-known publicized biometrics method is fingerprint identification.

The fingerprint usually shown Dark lines series that determine peaking portion of friction ridge skin, high, valleys and ridges in between shown as white space , they are low friction ridge skin shallow portion.

Techniques of fingerprint matching;

  • Pattern matching.
  • Minutiae –based matching.

Features of OCR:

  • Flexibility.
  • Auto detection.
  • Font Independent.
  • Portability.
  • Barcode.
  • No training.

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