Computer Graphics, Computer vision and Image processing

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 of image processing may be either an image or a set of characteristics orparameters related
to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and
applying standard signal-processing techniques to it.

Image processing usually refers to digital image processing, but optical and analog
image processing also are possible. This article is about general techniques that apply to all of them. The acquisition of images (producing the input image in the first place) is referred to as imaging.

Computer Graphics

Computer graphics is a sub-field of computer
science which studies methods for digitally synthesizing and manipulating visual content. Although the term often refers to the study of 3D
computer graphics, it also encompasses two-dimensional
graphics and image
processing. (http://en.wikipedia.org/wiki/Computer_graphics_(computer_science))

Computer Vision

Computer vision is a field that includes methods for acquiring, processing,
analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g.,
in the forms of decisions.



http://en.wikipedia.org/wiki/Computer_vision

Computer vision is, in some ways, the inverse of computer
graphics. While computer graphics produces image data from 3D models, computer vision often produces 3D models from image data. There is also a trend towards a combination of the
two disciplines, e.g., as explored inaugmented
reality.

Image processing and image
analysis tend to focus on 2D images, how to transform one image to another, e.g., by pixel-wise operations such as contrast enhancement, local operations such as edge extraction or noise removal, or geometrical transformations such as rotating
the image. This characterization implies that image processing/analysis neither require assumptions nor produce interpretations about the image content.
Computer vision includes 3D analysis from 2D images. This analyzes the 3D scene projected onto one or several images, e.g., how to reconstruct structure or other information about the 3D scene from one or several images.
Computer vision often relies on more or less complex assumptions about the scene depicted in an image.
Machine vision is the process of applying a range of technologies & methods to provide imaging-based
automatic inspection, process control and robot guidance[7] in
industrial applications.[8] Machine
vision tends to focus on applications, mainly in manufacturing, e.g., vision based autonomous robots and systems for vision based inspection or measurement. This implies that image sensor technologies and control theory often are integrated with the
processing of image data to control a robot and that real-time processing is emphasised by means of efficient implementations in hardware and software. It also implies that the external conditions such as lighting can be and are often more controlled in machine
vision than they are in general computer vision, which can enable the use of different algorithms.
There is also a field called imaging which primarily focus on the process of producing images,
but sometimes also deals with processing and analysis of images.
(http://en.wikipedia.org/wiki/Computer_vision)