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Bio-Inspired Asynchronous Pixel Event Tricolor Vision Sensor
IEEE Transactions on Biomedical Circuits and Systems
|August 13, 2013
Summary
This study presents a novel vision sensor prototype using stacked photodiodes and Address Event Representation (AER) for efficient data transmission. The sensor achieves high dynamic range and color approximation, enabling near-infrared detection and motion direction encoding.
Area of Science:
- Optoelectronics
- Sensor Technology
- Biologically Inspired Computing
Background:
- Traditional vision sensors face limitations in dynamic range and data processing efficiency.
- Bio-inspired asynchronous communication protocols offer potential for low-power, high-speed data acquisition.
Purpose of the Study:
- To develop and evaluate a novel vision sensor prototype integrating stacked photodiodes with Address Event Representation (AER).
- To assess the sensor's capabilities in color approximation, near-infrared (NIR) detection, and motion direction encoding.
Main Methods:
- Implementation of a 22x22 pixel array using stacked photodiodes in a 90nm CMOS process.
- Utilizing bio-inspired asynchronous pixel event communication via AER.
- Employing Pulse Frequency Modulation (PFM) or Time-to-First-Spike (TFS) pixel modes.
- Applying heuristic linear combination for RGB color approximation and analyzing update rate asymmetry for motion encoding.
Main Results:
- Achieved a dynamic range exceeding 60 dB with a 28% pixel fill factor.
- Demonstrated RGB color approximation using inherent pseudo-colors.
- Successfully processed sensor outputs for NIR radiation detection without external filters.
- Enabled color-encoded direction of motion detection through asymmetric update rates.
Conclusions:
- The prototype vision sensor demonstrates significant potential for advanced imaging applications.
- Integration of stacked photodiodes and AER offers a promising approach for high-performance, low-power vision systems.
- The sensor's multi-modal capabilities (color, NIR, motion) open avenues for diverse applications in robotics and machine vision.
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