Camera Sensor Light Source Classification via Intensity Fluctuation
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Solution Overview
Problem
Existing automatic light control systems for motor vehicle headlights rely solely on light intensity measurement, failing to distinguish between reflectors, motor vehicle headlights, and other light sources, leading to dysfunction.
Innovation Solution
A method using a camera sensor system to detect and categorize points of light by analyzing intensity fluctuations, shape, and movement, distinguishing between reflectors and motor vehicle lights through variance calculation and threshold-based classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only light intensity is measured, then the measurement system is simple, but the light source type cannot be classified leading to system dysfunction
Solution Approach 1:
The patent transitions from single-dimensional light intensity measurement to multi-dimensional analysis by incorporating temporal dimension (intensity fluctuations over time) and spatial dimension (movement patterns across image sequence). This allows differentiation between light sources based on their dynamic characteristics rather than static intensity alone.
Solution Approach 2:
The patent changes the measured parameters from simple light intensity to include intensity fluctuation variance and movement characteristics. By analyzing how intensity varies over time and space, the system can distinguish between reflectors (low fluctuation) and motor vehicle lights (high fluctuation) without requiring complex hardware.
2Measurement precision
If a camera sensor system is used to detect and categorize points of light, then light source classification accuracy is improved, but the device complexity increases
Solution Approach 1:
The system uses the camera's inherent capabilities to capture image sequences and automatically extracts features (intensity, position, movement) through algorithmic analysis. The camera serves multiple functions: capturing spatial information, temporal sequences, and intensity data, eliminating the need for separate sensors for each measurement type.
Solution Approach 2:
The camera sensor system performs multiple detection functions simultaneously - it captures spatial position, temporal intensity variations, and movement patterns using a single device. This multi-functional approach reduces overall system complexity compared to using separate specialized sensors for each measurement type.
3Reliability
If intensity fluctuation analysis is performed to distinguish light sources, then classification reliability is improved, but the processing complexity increases
Solution Approach 1:
The patent replaces complex mechanical or hardware-based classification systems with computational analysis of intensity fluctuation patterns. By using variance calculation and threshold-based classification algorithms, the system achieves reliable light source differentiation through software processing rather than complex hardware mechanisms.
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
Effectively differentiates between reflectors and motor vehicle headlights, improving the reliability of automatic light control systems by accurately identifying light sources based on intensity patterns and movement analysis.
Implementation Method 1
an image sequence of the motor vehicle environment is recorded with a camera sensor
Implementation Method 2
The intensity of a pursued point of light is determined in at least two images, and the intensity fluctuation is analysed
Data Source
AI summary
A method for detecting and categorizing points of light for a motor vehicle with a camera sensor directed towards the motor vehicle environment is presented. Here, at least one first category for passive, illumined reflectors and at least one second category for self-radiating, moving lights, in particular motor vehicle lights, is provided. For this purpose, the time progression of the intensity of a point of light is analysed. On the basis of the intensity fluctuation, points of light are categorized as motor vehicle lights or as reflectors.