Parking Object Detection with Dynamic Sensor Weighting
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Solution Overview
Problem
Existing methods for detecting objects on parking areas face challenges due to environmental conditions like solar radiation, rain, snow, and fog, which impair the image quality of imaging sensors, leading to suboptimal object detection.
Innovation Solution
The method employs multiple imaging sensors with overlapping detection ranges, where images from sensors with limited quality due to environmental conditions are weighted less strongly during processing, and uses image processing to detect and compensate for degraded image quality, including comparisons with reference images and calculations based on sensor position and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple imaging sensors are used to detect objects on the parking area, then the detection coverage and reliability are improved, but the image quality may be impaired by environmental conditions such as solar radiation, rain, snow, or fog
Solution Approach 1:
The system dynamically adjusts the weighting of images from different imaging sensors based on real-time environmental conditions. When certain sensors are affected by solar radiation, rain, snow, or fog, their image weights are reduced automatically, allowing the system to adapt to changing conditions and maintain reliable object detection.
Solution Approach 2:
The system changes the parameter of image weighting dynamically. By adjusting the weight parameter of images from different sensors based on environmental conditions, the system optimizes detection accuracy without requiring additional hardware or complex sensor arrangements.
2Measurement precision
If images from all imaging sensors are weighted equally during processing, then the processing is simpler, but the detection accuracy deteriorates when some sensors are affected by environmental conditions
Solution Approach 1:
The system introduces a weight parameter for images from different imaging sensors and dynamically adjusts this parameter based on environmental conditions. This allows the system to prioritize high-quality images while maintaining a relatively simple processing framework that doesn't require complex algorithms or additional hardware.
Solution Approach 2:
The system uses feedback from environmental condition detection to adjust image weighting. By monitoring conditions such as solar radiation, rain, snow, or fog, the system automatically adjusts the weights of images from affected sensors, creating a feedback loop that improves detection accuracy without requiring manual intervention or complex processing.
3Area of stationary object
If imaging sensors are positioned to maximize coverage of the parking area, then more areas are monitored, but the sensors are more likely to be exposed to environmental conditions that degrade image quality
Solution Approach 1:
The system dynamically adjusts the weighting of images from different imaging sensors based on real-time environmental conditions. When certain sensors are affected by solar radiation, rain, snow, or fog, their image weights are reduced automatically, allowing the system to maintain wide coverage while compensating for quality issues in specific areas.
Solution Approach 2:
The system applies different quality standards and weighting to images from different sensors based on their specific environmental conditions. Rather than treating all images uniformly, the system evaluates each sensor's local conditions and adjusts weighting accordingly, allowing wide coverage while maintaining high detection accuracy in affected areas.
Data Source
AI summary
A method for detecting objects on a parking area for vehicles with the aid of image processing of images from at least two imaging sensors, detection ranges of the imaging sensors overlapping at least partially. The images of an imaging sensor whose image quality is limited by environmental conditions are weighted less strongly for the detection of objects on the parking area during image processing than images of an imaging sensor whose image quality is not limited by environmental conditions. A processing unit, a program, and an overall system for carrying out the method are also described.