Movement of object is basic task need for many image and video processing applications such as satellite imaging,biometrics identification,video surveillance,automated inspection in industry products,etc.MATLAB makes use of search path to locate M-files and other MATLAB related files which are in directories of computer file system.The file that run in MATLAB should present in the directory of search path.MATLAB is a good environment for fast algorithm development and perceived as slow so that it is not fit for medical  processing which has large data sets.for example high resolution CT image sets which has 512X512 algorithms are used to perform image processing on digital image processing has many advantages when compared to analog image processing which act as the subfield of digital signal processing.Hence a numerous algorithms are applied to two input data and so one can avoid problems like signal distortion and build up of noise during processing.


Projects on Matlab  has uses in the following fields,

  • Satellite image processing
  • Face detection,feature detection,face identification
  • Photography and printing
  • Medical image processing
  • Microscope image processing

The images can be divided by using the following types in image processing.they are

True color.


Grey scale.


True color: 

It is true RGB color image.


It’s a pseudocode image

Gray scale:

 It’s gray level image or gray scale image


It’s bilevel image.

Filtering is used to remove noise present in images.separable 2-d filtering is the one which separates rows and column which is better than the more general non-separable 2-d filtering. the function that is the integral or addition of two component function and that calculates how much overlap function is shifted over another is described as convolution. mean squared error is a error in imageprocessing.It is the cumulated squared error between the original image and reconstructed get good performance in a wide range of inputs the image processing using matlab,robust compiler system that leverages the right combination of task, pipeline parallelism and data.due to increasing security demands and law enforcement applications and its potential commercial FACE recognition has become a very active area in recent years.

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