Event-Based Vision Sensor Window Masking for Flicker Detection
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Solution Overview
Problem
Event-based vision sensors struggle to capture moving objects in flicker environments due to flicker interference, which affects data output and prevents accurate observation.
Innovation Solution
An event-based vision sensor (EVS) with a pixel array, window counter, on/off counter, and Identification of Condition (IoC) unit that distinguishes between flicker and non-flicker windows by counting events and masking or enabling pixel output based on event patterns, enhanced by a flicker detection unit and frequency calculation to improve robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If EVS outputs event signals in response to luminance changes, then high-speed and low-latency data output is achieved, but flicker interference prevents accurate observation of moving objects
Solution Approach 1:
The pixel array is divided into multiple windows, and event counting is performed separately for each window. This segmentation allows the system to identify flicker patterns in specific regions while maintaining high-speed event-based detection across the entire sensor array.
Solution Approach 2:
An event counter unit is introduced as an intermediary component between the EVS panel and the output stage. This counter accumulates event signals and enables flicker detection through pattern analysis, acting as a mediator that preserves high-speed detection while adding reliability through statistical analysis of event sequences.
2Productivity
If EVS detects all luminance changes, then high-speed data output is maintained, but flicker events are indistinguishable from actual object movement
Solution Approach 1:
The event counter unit performs preliminary counting and accumulation of event signals before final output determination. By accumulating events over a defined period and analyzing patterns in advance, the system can distinguish flicker from genuine motion while maintaining high detection sensitivity.
Solution Approach 2:
The system uses feedback from accumulated event counts to determine whether to mask or output signals. The counter unit provides feedback information about event patterns, enabling the system to adaptively distinguish between flicker interference and actual object movement based on historical event data.
3Object-affected harmful factors
If window masking is applied to suppress flicker, then flicker interference is reduced, but potential moving objects in masked regions may be missed
Solution Approach 1:
The window masking operation is dynamic rather than static. The system continuously monitors event patterns in each window and adjusts masking status in real-time based on detected flicker conditions. This dynamic approach allows the system to mask windows only when flicker is detected, preserving the ability to detect moving objects when conditions are normal.
Solution Approach 2:
Each window effectively serves itself by having its own event counter track local event patterns. The counter unit for each window independently determines whether that specific window exhibits flicker characteristics, allowing localized masking decisions that preserve detection capability in non-flicker regions while suppressing interference in affected areas.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables high-speed, low-latency data output in flicker environments, allowing accurate detection of moving objects while suppressing flicker interference, thereby maintaining image quality and enabling small-size image rotation correction.
Implementation Method 1
A photodetector of the sensor converts the linear current output of the Photo Diode section into a log voltage in response to the intensity of the incident light
Data Source
AI summary
An event-based vision sensor (EVS) is provided. The EVS includes an EVS panel that includes a pixel array, a window counter unit, an on/off counter unit, and an Identification of Condition (IoC) unit. The window counter unit partitions the pixel array into a plurality of windows. The on/off counter unit counts on-events and off-events occurring for each window in the plurality of windows. The IoC unit determines whether to mask each of the corresponding windows in accordance with the count.