COMPUTER VISION AND IMAGE PROCESSING

A human eye has between six and seven million cone cells, containing one of three colour-sensitive proteins known as opsins. When photons of light hit these opsins, they change shape, triggering a cascade that produces electrical signals, which in turn transmit the messages to the brain for interpretation.

This whole process is a very complex phenomenon and making a machine to interpret this at a human level has always been a challenge. The motivation behind the modern-day machine vision system lies at the core of emulating human vision for recognising patterns, faces and rendering 2D imagery from a 3D world into 3D.

There is a lot of overlap between image processing and computer vision at the conceptual level and the jargon, often misunderstood, is being used interchangeably.

Image Processing
Digital image processing was pioneered at NASA’s Jet Propulsion Laboratory in the late 1960s, to convert analogue signals from the Ranger spacecraft to digital images with computer enhancement. Now, digital imaging has a wide range of applications, with particular emphasis on medicine. Well-known uses for it include Computed Aided Tomography (CAT) scanning and ultrasounds.

Image Processing is mostly related to the usage and application of mathematical functions and transformations over images regardless of any intelligent inference being done over the image itself. It simply means that an algorithm does some transformations on the image such as smoothing, sharpening, contrasting, stretching on the image.

Computer Vision
Computer vision comes from modelling image processing using the techniques of machine learning. Computer vision applies machine learning to recognise patterns for interpretation of images. Much like the process of visual reasoning of human vision; we can distinguish between objects, classify them, sort them according to their size, and so forth. Computer vision, like image processing, takes images as input and gives output in the form of information on size, colour intensity etc.