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Image Processing:
Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame. The output may be either an image or a set of characteristics or parameters related to the image.
Image processing can also be stated as the process of study of any algorithm that takes image as input and return a image back.
It’s a method to change an image into digital form and execute some operations on it, in order to get an improved image or to mine some constructive information from it.
It has three steps
  • Image is imported through optical scanner or directly through digital photography
  • Imported image is analyzed and manipulated for enhancements and data compressions. The image can also be analyzed for discovering new patterns.
  • Output may be a report or an altered / modified image based on the techniques that are applied.
» The two main color spaces in Image processing are RGB and CMYK


The RGB color model relates very closely to the way we recognize color with the R, G, and B receptors in our retinas. It’s the fundamental color model used in television or any other medium that projects color with RGB which uses additive color integration. Computers and web graphics use this basic color model but it cannot be used for print production.

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Overlapping layers of varying percentages of transparent cyan (C), magenta (M) and yellow (Y) inks is laid down by the 4-colour CMYK model used in printing. A layer of black (K) ink can be added. The subtractive color model is used by The CMYK model.

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Block Diagram
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1. Image-to-image transformations
2. Image-to-information transformations
3. Information-to-image transformations

Image - to - image Transformation

  • Enhancement
  • Restoration
  • Scaling, sizing, zooming

Image - to - information Transformation

  • Histogram
  • Image compression
  • Image analysis
  • Computer Aided Design (CAD) & Diagnosis

Information - to – image Transformation

  • Decompression
  • Reconstruction
  • Computer graphics, animation, virtual reality
Real Time Examples
  • Computer Graphics
  • Automatic Number Plate Recognition
  • Biometrics
  • Surveillance
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