Journal
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
Volume 26, Issue 12, Pages 2816-2829Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVLSI.2018.2829918
Keywords
Artificial retina; memristor; neuromorphic vision; sensor systems; silicon retina
Funding
- National Research Foundation of Korea - Korean Government [NRF-2017R1D1A1A09000613]
- DFAT Australia-Korea Foundation [AKF00640]
- iDataMap Corporation
- Grant UWA RCA 2017
Ask authors/readers for more resources
The development of a bioinspired image sensor, which can match the functionality of the vertebrate retina, has provided new opportunities for vision systems and processing through the realization of new architectures. Research in both retinal cellular systems and nanodriven memristive technology has made a challenging arena more accessible to emulate features of the retina that are closer to biological systems. This paper synthesizes the signal flow path of photocurrent throughout a retina in a scalable 180-nm CMOS technology, which initiates at a 128 x 128 active pixel image sensor, and converges to a 16 x 16 array, where each node emits a spike train synonymous to the function of the retinal ganglionic output cell. This signal can be sent to the visual cortex for image interpretation as part of an artificial vision system. Layers of memristive networks are used to emulate the functions of horizontal and amacrine cells in the retina, which average and converge signals. The resulting image matches biologically verified results within an error margin of 6% and exhibits the following features of the retina: lateral inhibition, asynchronous adaptation, and a low-dynamic-range integration active pixel sensor to perceive a high-dynamic-range scene.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available