Computer Vision

• Computer vision is concerned with modeling and replicating human vision using computer software and hardware. Formally if we define computer vision then its definition would be that computer vision is a discipline that studies how to reconstruct, interrupt and understand a 3d scene from its 2d images in terms of the properties of the structure present in scene.

• Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions.

• Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that can interface with other thought processes and elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.

• Computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply its theories and models for the construction of computer vision systems.

Two important specifications in any vision system are the sensitivity and the resolution:

• Sensitivity is the ability of a machine to see in dim light, or to detect weak impulses at invisible wavelengths. 

• Resolution is the extent to which a machine can differentiate between objects. In general, the better the resolution, the more confined the field of vision.

• Sensitivity and resolution are interdependent. All other factors held constant, increasing the sensitivity reduces the resolution, and improving the resolution reduces the sensitivity.

The term machine vision is often associated with industrial applications of a computer's ability to see, while the term computer vision is often used to describe any type of technology in which a computer is tasked with digitizing an image, processing the data it contains and taking some kind of action.

Examples of applications of computer vision include systems for:

• Automatic inspection, e.g. in manufacturing applications.

• Assisting humans in identification tasks e.g. a species identification system

• Controlling processes  e.g. an industrial robot.

• Detecting events  e.g. or visual surveillance or people counting.

• Interaction e.g. as the input to a device for computer-human interaction.

• Modeling objects or environments e.g. medical image analysis or topographical modeling.

• Navigation e.g. by an autonomous vehicle or mobile robot.

• Organizing information  e.g. for indexing databases of images and image sequences.

     
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     Next week I will post more about AI...so stay tuned!