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Differentiating Computer Vision & Image Processing

Differentiating Computer Vision & Image Processing

The structure of a human eye is so complex that is having around six to seven million cone cells which contain Osins, a color sensitive protein. Whenever the photons from the light strike these Opsins they tend to change its shape, triggering a cascade that produces electrical signals that relay the messages to the brain for interpretation.

Since the beginning of the 21st century, extensive research work is being carried out to make the machines interpret the same phenomenon as functioning of a human eye. Inspired from the brilliance of human vision, experts are working towards presenting machines with Computer Vision for recognizing patterns, faces and rendering 2D imagery from a 3D world into 3D.

At its core there is a lot of overlap between image processing and computer vision. In this blog post, let’s see the fundamental differences between Computer Vision & Image Processing.

  • Image Processing

The foundation for Digital image processing was laid back in 1960s at NASA’s Jet Propulsion Laboratory. They used Image Processing for converting analogue signals from the Ranger spacecraft to digital images with computer enhancement. The applications of Digital Imaging are of impeccable value especially in the medicine industry like Computed Aided Tomography (CAT) scanning and ultrasounds.

Image Processing makes use of applications related to mathematical functions and transformations over images which is done irrespective of any intelligent inference being done over the image itself. This simply implies that the algorithms would be performing some sort of transformations on the image such as smoothing, sharpening, contrasting & stretching.

Differentiating Computer Vision & Image Processing

The most commonly used techniques for the process of Digital Image Processing are

  • Hidden Markov models
  • Image editing and restoration
  • Linear filtering and Bilateral filtering
  • Neural networks
  • Computer Vision

Computer vision comes from modeling image processing by making use of various modeling techniques in Machine Learning. With the help of models in Machine Learning, Computer vision applies machine learning to recognize patterns for interpretation of images. With Machine Learning, we can present machines with the abilities to distinguish between objects, classify them, sort them according to their size, and so forth.

In order to excel in a career as a Data Scientist or AI expert having knowledge of these techniques is very crucial. Analytics Path offers the most advanced analytics-based learning program of Data Science Training In Hyderabad which helps the analytics career enthusiasts to master the knowledge of these technologies.