Vehicle Light Source Detection Using Shadow Analysis
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Solution Overview
Problem
Existing vehicle light source detection systems fail to accurately identify motorcycle light sources and often incorrectly detect non-vehicle light sources as vehicle light sources, resulting in low detection reliability.
Innovation Solution
A vehicle-mounted apparatus that includes an image acquiring means, light source extracting means, probability calculating means, dark section extracting means, and probability correcting means to differentiate vehicle light sources by analyzing light source parameters such as color, shape, brightness, position, and size, and adjusts probabilities based on the presence of shadows and similar-color reflected light to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If light source detection is based on simple pair identification, then detection process is simple, but detection reliability is low because motorcycles and other non-pair light sources are missed and false detections occur
Solution Approach 1:
The patent transitions from two-dimensional light source parameter analysis (color, brightness, position, size) to three-dimensional analysis by incorporating shadow detection as an additional spatial dimension. The shadow extraction unit detects dark regions below light sources, and the probability correction unit uses this vertical spatial information to differentiate vehicle light sources from non-vehicle light sources, significantly improving detection reliability without excessive complexity increase
Solution Approach 2:
The patent introduces probability values as a new parameter to quantify the likelihood of a light source being from a vehicle. The probability calculation unit computes initial probabilities based on light source parameters (color, shape, brightness, position, size), and the probability correction unit adjusts these probabilities based on shadow detection results. This parameter transformation enables systematic differentiation between vehicle and non-vehicle light sources
2Measurement precision
If probability correction based on shadow detection is applied, then vehicle light source detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent divides the detection process into distinct functional modules: light source extraction unit, shadow extraction unit, probability calculation unit, and probability correction unit. Each module performs a specific task, making the complex processing pipeline manageable and maintainable. The segmentation allows parallel processing of light source parameters and shadow information, reducing overall processing complexity while maintaining high accuracy
Data Source
AI summary
In a light control system, a captured image of a cruising direction of a vehicle is acquired, and a light source is extracted from the captured image. A probability for estimating a light source to be a vehicle light source originating from a vehicle is calculated based on light source parameters for differentiating the light source. A dark section that is darker than the periphery and is present below the light source in the captured image is extracted. The probability is set to be higher for the light source of which the dark section is extracted. The light source having a probability that is a reference value set in advance or higher is estimated to be a light source of another vehicle. When the dark section that is detected as a shadow of a vehicle is detected, the probability of the light source being a vehicle light source is set to be high.