Image Processing and Computer Vision

Computer imaging of a honeybee brain using Amira software. Photo credit Christian Wietholt.

Humans are very visually-orientated creatures in general. Since sight is one of our foremost senses, it should come as no surprise that the twin areas of image processing and computer vision are quite large, and have far-reaching uses.

Many decisions involving gathered statistics are made with visual aids. By acquiring, processing and analyzing images produced by software one can understand high-dimensional data from the real world, or better see patterns. Perhaps more interesting though is the increasing ability of computers to 'understand' their own produced images as well. It has become a theme to duplicate the characteristics of human perception and analysis using machines for efficiency via automation. Machine understanding occurs through analyzing the geometry, physics, statistics involved in an image representation of a situation, and also requires some use of learning theory.

One of the most important uses of image processing and computer vision is in the field of medicine. Here, x-rays and ultrasounds are just the most well-known examples of a huge range of technical images that physicians and their kind use to assess and diagnose patients. The health industry funds a lot of imaging research for this reason, focusing on enhancement and discovering what new information can be gleaned from the images our new machines produce, particularly in radiology.

Other real-world applications and implementations of computer vision are as varied as any field of computer technology. Some units are stand-alone, specifically and exclusively designed for image processing, while others will act as a sub-system of a larger design. The amount that these creations can 'understand' and therefore analyse their images is also highly variable, and is expected to increase alongside the field of artificial intelligence.

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