All-Digital Event-Based Vision Sensor With Multi-Event Generation for Motion/Vibration-Adaptive Detection

This article presents an all-digital event-based vision sensor (EVS) using single-photon avalanche diode (SPAD) pixels. The proposed sensor introduces a multi-event generation method that enables the detection of light intensity changes across multiple levels, facilitating advanced event-image processing techniques. The three core processing techniques implemented are event-driven threshold control (EDTC), vibration event noise (VEN) filtering, and adaptive frame-rate control (AFRC). Using the multi-event-based processing, the sensor can dynamically adjust the event-generation threshold (TH), optimize the frame rate, and filter out noise caused by vibrations, thereby enhancing the accuracy of object detection in various challenging environments. EDTC ensures a consistent event rate regardless of the scene’s contrast or lighting conditions, reducing the overall event rate by 55.66%. VEN filtering successfully eliminates 67.25% of the noise generated by vibrations when the sensor module is exposed to constant vibrations, and AFRC optimizes the frame rate based on the relative speed of moving objects, minimizing motion blur and the loss of event data.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Solid-State Circuits
Published
2025-02-21
DOI
https://doi.org/10.1109/jssc.2025.3536184
Citations
2
Primary Topic
CCD and CMOS Imaging Sensors
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

All-Digital Event-Based Vision Sensor With Multi-Event Generation for Motion/Vibration-Adaptive Detection

Jung‐Hoon Chun, Heesung Lee, Houk Lee, Junhee Cho et al.
2 citations
IEEE Journal of Solid-State Circuits
CCD and CMOS Imaging Sensors
1.46
article

All-Digital Event-Based Vision Sensor With Multi-Event Generation for Motion/Vibration-Adaptive Detection

Jung‐Hoon Chun, Heesung Lee, Houk Lee, Junhee Cho, Jaehyuk Choi, Seong‐Jin Kim, Jinpyo Han
article en
2 citations

Abstract

This article presents an all-digital event-based vision sensor (EVS) using single-photon avalanche diode (SPAD) pixels. The proposed sensor introduces a multi-event generation method that enables the detection of light intensity changes across multiple levels, facilitating advanced event-image processing techniques. The three core processing techniques implemented are event-driven threshold control (EDTC), vibration event noise (VEN) filtering, and adaptive frame-rate control (AFRC). Using the multi-event-based processing, the sensor can dynamically adjust the event-generation threshold (TH), optimize the frame rate, and filter out noise caused by vibrations, thereby enhancing the accuracy of object detection in various challenging environments. EDTC ensures a consistent event rate regardless of the scene’s contrast or lighting conditions, reducing the overall event rate by 55.66%. VEN filtering successfully eliminates 67.25% of the noise generated by vibrations when the sensor module is exposed to constant vibrations, and AFRC optimizes the frame rate based on the relative speed of moving objects, minimizing motion blur and the loss of event data.

IEEE Journal of Solid-State CircuitsVol. 60(4)
Solid (South Korea) (KR), Ulsan National Institute of Science and Technology (KR), Sungkyunkwan University (KR)
Affordable and clean energy
Openalex Percentile: Top 19%
CCD and CMOS Imaging Sensors
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

All-Digital Event-Based Vision Sensor With Multi-Event Generation for Motion/Vibration-Adaptive Detection — Jung‐Hoon Chun, Heesung Lee, et al. · IEEE Journal of Solid-State Circuits (2025) | TGRS Research Map | TGRS