Event Detection Sensitivity Control for Weather Noise
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Event detection devices mounted on mobile units, such as vehicles, face challenges in accurately recognizing objects in bad weather conditions like rain or snow due to the detection of water droplets as events, leading to decreased accuracy in object recognition.
Innovation Solution
An imaging system with an event detection device that adjusts its detection sensitivity based on external information, such as weather conditions, using a controller to raise or lower the detection threshold to minimize noise from water droplets and ensure accurate object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the detection sensitivity of the event detection device is increased to improve object detection capability, then the detection precision is improved, but water droplets in bad weather are more likely to be detected as events, causing noise and decreasing recognition accuracy
Solution Approach 1:
The patent applies dynamics by making the detection threshold adjustable rather than fixed. The controller dynamically changes the detection threshold based on weather conditions (rain, snow, fog) to optimize the balance between detecting actual objects and filtering out water droplet noise. This resolves the contradiction by allowing high sensitivity when needed while suppressing false positives from water droplets in bad weather.
Solution Approach 2:
The patent changes the detection threshold parameter based on external weather information. By adjusting this key parameter, the system adapts its sensitivity to match environmental conditions, thereby maintaining high object detection accuracy while reducing noise from water droplets during precipitation or foggy conditions.
2Object-affected harmful factors
If the detection threshold is raised to reduce noise from water droplets, then the harmful factors are reduced, but the detection sensitivity decreases, potentially missing actual objects
Solution Approach 1:
The system dynamically adjusts the detection threshold based on real-time weather conditions rather than using a fixed high threshold. This allows the system to maintain low thresholds (high sensitivity) during clear weather for accurate object detection, and only raise thresholds during bad weather when water droplet noise becomes problematic, thus resolving the contradiction between noise reduction and detection sensitivity.
Solution Approach 2:
The controller receives feedback about weather conditions (rain, snow, fog detection) and adjusts the detection threshold accordingly. This feedback mechanism ensures that the threshold is raised only when necessary to filter water droplet noise, while maintaining optimal sensitivity for object detection during favorable weather conditions.
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
The system effectively reduces noise from water droplets in bad weather, enhancing the accuracy of object recognition by dynamically adjusting the detection sensitivity of the event detection device.
Implementation Method 1
an asynchronous imaging device called a dynamic vision sensor (DVS). An asynchronous imaging device can detect an event that a change in the luminance of a pixel that photoelectrically converts incident light exceeds a predetermined threshold
Data Source
AI summary
An imaging system of the present disclosure includes: an event detection device that detects an event; and a controller that controls the event detection device. The controller then controls the detection sensitivity of event detection being performed by the event detection device, on the basis of external information. Further, an object recognition system of the present disclosure includes: an event detection device that detects an event; a controller that controls the detection sensitivity of event detection being performed by the event detection device, on the basis of external information; and a recognition processing unit that performs object recognition in an event, on the basis of an event signal output from the event detection device.