Based on the digital microprocessors, the real-time vision systems were developed with all the equipment integrated into the vehicle. The highly developed vertebrates in the larger part of the brain are devoted to visualizing the data processed from motion control, scene understanding, and behavioral decision.
Many biologists have considered vision as one of the driving factors in developing intelligence evolved by individuals with complex brains. Many different types of eyes are found per individual in a wide range of classes among different animals as well as humans.
The high-performance locomotives have the capacity on every possible area to focus radially with different resolutions in the images. This modality of this kind of vision must have advantages that evolve over many generations.
The rotation of the eye is pointed by the direction employed by the fovea for accurate vision. This vision comprises less than 1% of the retinal size, though uses over 50% of the visual cortex in the brain.
By this, Image preprocessing can be performed in the eye so that the number of nerves feeding the primary visual cortex at the backside of the human brain is reduced by two orders of magnitude.
When compared to the number of photoreceptors in the eye, edge orientations are coded directly in the eye to achieve this reduction.
The eye would not take a photographic image of the environment, but rather it can produce up to 100 extremely compressed full images of low precision for the peripheral FoV parallely; in addition to this, with high resolution are generated by foveal perception with three to four small areas.
These data can be compared with existing images in the actual imagination process, and are transformed into the actual perception of the environment.
Meanwhile, In several research institutes and universities, several attempts were made in order to develop software for understanding and interpreting image sequences on computers that were actually available. This typical cycle times for a single perception step which were in the range of seconds to minutes.
Several groups from Artificial intelligence and Computer Science have started investigating rather complex vision tasks at a much slowed-down rate on available computing hardware.
At the same time, massively parallel computer systems were investigated to analyze various sequences of digital images. Temporal aspects were considered separately in a second step that differentiates the interpretation results of consecutive images which had to be interpreted either as changes due to ego-motion or movements of objects in the mapped 3-D scene.
A completely different approach has been made, coming from systems dynamics and control engineering, including optimal control.
The technical vision systems based on silicon molecules are not mandatory to separate processing of image data both in the eye and in the visual cortex of the human vision system partially based on carbon molecules. In this sequence, computers and sensors may be kept separately.
Requirements that need to be fulfilled are outlined, as several high-resolution images may be communicated in parallel from the sensors to the computing elements. However, the saccadic type of multi-focal image sequence analysis may be of advantage in technical systems too.