Bio-inspired Electronics for Micropower Vision Processing
Author(s)
Constandinou, TG
Type
Thesis
Abstract
Vision processing is a topic traditionally associated with neurobiology; known to encode,
process and interpret visual data most effectively. For example, the human retina;
an exquisite sheet of neurobiological wetware, is amongst the most powerful and efficient
vision processors known to mankind. With improving integrated technologies, this has
generated considerable research interest in the microelectronics community in a quest to
develop effective, efficient and robust vision processing hardware with real-time capability.
This thesis describes the design of a novel biologically-inspired hybrid analogue/digital
vision chip ORASIS1 for centroiding, sizing and counting of enclosed objects. This chip is
the first two-dimensional silicon retina capable of centroiding and sizing multiple objects2
in true parallel fashion. Based on a novel distributed architecture, this system achieves
ultra-fast and ultra-low power operation in comparison to conventional techniques.
Although specifically applied to centroid detection, the generalised architecture in fact
presents a new biologically-inspired processing paradigm entitled: distributed asynchronous
mixed-signal logic processing. This is applicable to vision and sensory processing applications
in general that require processing of large numbers of parallel inputs, normally
presenting a computational bottleneck.
Apart from the distributed architecture, the specific centroiding algorithm and vision
chip other original contributions include: an ultra-low power tunable edge-detection circuit,
an adjustable threshold local/global smoothing network and an ON/OFF-adaptive spiking
photoreceptor circuit.
Finally, a concise yet comprehensive overview of photodiode design methodology is provided
for standard CMOS technologies. This aims to form a basic reference from an engineering
perspective, bridging together theory with measured results. Furthermore, an
approximate photodiode expression is presented, aiming to provide vision chip designers
with a basic tool for pre-fabrication calculations.
process and interpret visual data most effectively. For example, the human retina;
an exquisite sheet of neurobiological wetware, is amongst the most powerful and efficient
vision processors known to mankind. With improving integrated technologies, this has
generated considerable research interest in the microelectronics community in a quest to
develop effective, efficient and robust vision processing hardware with real-time capability.
This thesis describes the design of a novel biologically-inspired hybrid analogue/digital
vision chip ORASIS1 for centroiding, sizing and counting of enclosed objects. This chip is
the first two-dimensional silicon retina capable of centroiding and sizing multiple objects2
in true parallel fashion. Based on a novel distributed architecture, this system achieves
ultra-fast and ultra-low power operation in comparison to conventional techniques.
Although specifically applied to centroid detection, the generalised architecture in fact
presents a new biologically-inspired processing paradigm entitled: distributed asynchronous
mixed-signal logic processing. This is applicable to vision and sensory processing applications
in general that require processing of large numbers of parallel inputs, normally
presenting a computational bottleneck.
Apart from the distributed architecture, the specific centroiding algorithm and vision
chip other original contributions include: an ultra-low power tunable edge-detection circuit,
an adjustable threshold local/global smoothing network and an ON/OFF-adaptive spiking
photoreceptor circuit.
Finally, a concise yet comprehensive overview of photodiode design methodology is provided
for standard CMOS technologies. This aims to form a basic reference from an engineering
perspective, bridging together theory with measured results. Furthermore, an
approximate photodiode expression is presented, aiming to provide vision chip designers
with a basic tool for pre-fabrication calculations.
Date Issued
2005-10-31
Date Awarded
2005-10
Citation
PhD Thesis, 2005
Publisher
Imperial College of Science, Technology and Medicine, University of London
Journal / Book Title
PhD Thesis
Format Extent
10014141 bytes
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Toumazou, Christofer
Sponsor
Toumaz Technology Ltd,
Creator
Constandinou, Timothy
Identifier
http://spiral.imperial.ac.uk/handle/10044/1/1290
Publisher Department
Electrical and Electronic Engineering
Publisher Institution
University of London - Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)
Place of Publication
London, UK
Publication Status
Published