An artificial retina chip using switch-selective resistive network for intelligent sensor systems

Authors:
Jae-Sung Kong;Sang-Heon Kim;Jang-Kyoo Shin;Minho Lee
Affiliations:
Department of Electronics, Kyungpook National University, Daegu, South Korea;Department of Electronics, Kyungpook National University, Daegu, South Korea;Department of Electronics, Kyungpook National University, Daegu, South Korea;Department of Electronics, Kyungpook National University, Daegu, South Korea
Venue:
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Year:
2006

Citing 1
Cited 1

Analog VLSI and neural systems

Analog VLSI and neural systems

A 160×120 Edge Detection Vision Chip for Neuromorphic Systems Using Logarithmic Active Pixel Sensor with Low Power Dissipation

Neural Information Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We designed and fabricated a bio-inspired CMOS vision chip for edge detection using a switch-selective resistive network. A CMOS buffer circuit, which is embodied in the structure of a common drain amplifier, is commonly used for both raw and smoothed images by using additional switches. By using the switch-selective resistive network, the total number of MOSFETs in the unit pixel and fixed-pattern noise (FPN) was reduced. In addition, by applying the saturating resistive network, the chip outputs a uniform edge signal under various lighting conditions. From the experimental results of a fabricated one-dimensional array with 20 pixels, we could confirm the operation of the vision chip.