Camera-Based Debris Detection Using Height Features
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Solution Overview
Problem
Current advanced driver assistance systems (ADAS) and autonomous driving technologies face challenges in detecting and avoiding debris on roadways, which can lead to accidents and vehicle damage, due to the small size and varied types of debris, and often require multiple sensors and significant computational resources.
Innovation Solution
A camera-based debris detection system that uses image processing to determine height-based features and weighting factors to identify debris, employing strong and weak feature-based classifiers to detect debris in real-time with reduced hardware and computational costs, and can also detect potholes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors and complex computational systems are used to detect debris, then detection reliability is improved, but device complexity and computational resource requirements increase
Solution Approach 1:
The patent replaces complex multi-sensor mechanical systems with a camera-based optical system combined with image processing algorithms. The camera captures images of the road surface, and computer vision algorithms analyze these images to detect debris, substituting physical sensors with optical detection and computational analysis.
Solution Approach 2:
The system creates a digital copy of the road surface through camera imaging, then analyzes this visual representation to detect debris. Instead of directly interacting with or using multiple physical sensors on the road, the system works with a two-dimensional image copy that can be processed computationally to identify debris locations and characteristics.
2Measurement precision
If multiple sensors and significant computational resources are deployed, then debris detection accuracy is improved, but loss of energy and computational cost increase
Solution Approach 1:
The patent extracts only the essential visual features needed for debris detection from the captured images, such as color, texture, and shape characteristics. By focusing on these specific extracted features rather than processing the entire image data set, the system achieves accurate detection while minimizing computational energy consumption.
Solution Approach 2:
The system changes the parameters of analysis by converting physical debris properties into visual parameters that can be detected through image processing. Debris characteristics such as material composition, shape, and size are transformed into color, texture, and geometric parameters that can be efficiently analyzed using computer vision algorithms, reducing computational burden while maintaining detection accuracy.
Data Source
AI summary
In some examples, one or more processors may receive at least one image of a road, and may determine at least one candidate group of pixels in the image as potentially corresponding to debris on the road. The one or more processors may determine at least two height-based features for the candidate group of pixels. For instance, the at least two height-based features may include a maximum height associated with the candidate group of pixels relative to a surface of the road, and an average height associated the candidate group of pixels relative to the surface of the road. In addition, the one or more processors may determine at least one weighting factor based on comparing the at least two height-based features to respective thresholds, and may determine whether the group of pixels corresponds to debris based at least on the comparing.