Abstract
A review of current trends in biologically based computational visual sensors, also known as neuromorphic sensors, is presented. Neuromorphic sensors attempt to mimic the sensing and early visual-processing characteristics of living organisms. The objective of these sensors is to help reduce the computational load required for visual perception by extracting only information relevant to the post-processing stages. Furthermore, mechanisms for improving electronic imaging are also obtained by mimicking their biological counterparts. This paper provides the history and current practices for implementing neuromorphic sensors with (1) task-specific spatial variant layouts, (2) continuous time and steady-state phototransduction, (3) dynamic range compression using logarithmic and adaptive photoreceptors, and (4) early visual processing capabilities for focal plane edge, motion and orientation detection. For each of these functions, the practical considerations, the most successful methods and their future development are discussed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
