Computer vision is one of the most important fields for neural simulation. Neural Research is engaged in both the research and development of motion image analysis systems (scene analysis from fixed and mobile cameras), and biomedical image analysis (clinical diagnostics).

Machine vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos . From an engineering perspective, seeks to understand and automate the tasks that the human visual system can perform.

Computer vision activities include methods for acquiring , processing , analyzing and understanding digital images and extracting high definition data from the real world in order to produce numerical or symbolic information, for example in the form of decisions.

By "understanding" in this context we mean the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate actions.

This understanding of the image can be seen as discriminating symbolic information from image data using models built with the help of geometry, physics, statistics and learning theory.

The scientific discipline of computer vision makes use of the theory behind artificial systems that extract information from images.