Radar-Camera Object Detection for Floating Matter Identification
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Solution Overview
Problem
Existing object detection systems struggle to accurately identify floating matters in environments with no wind, as the rate of change in object size per unit of time does not exceed the predetermined threshold, leading to incorrect determinations.
Innovation Solution
An object detection method utilizing a radar and camera system to capture and analyze image differences before and after an object is detected, determining whether the object is floating matter by calculating brightness, chroma, and hue differences within a threshold, and employing vehicle control units to manage vehicle interactions based on these determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the rate of change in size of the detected object per unit of time is used to determine floating matters, then floating matters can be detected in windy conditions, but floating matters cannot be detected in environments with no wind where the rate of change does not exceed the threshold
Solution Approach 1:
The patent changes the detection parameter from rate of size change to image brightness difference. By comparing brightness values between images captured at different times, the system can detect floating matters regardless of wind conditions, as floating particles will always cause some brightness variation in the optical images.
Solution Approach 2:
The patent replaces the mechanical/radar-based detection method with an optical-based method. Instead of using radar to detect object size changes, the system uses camera-captured optical images and compares brightness differences, substituting a mechanical measurement approach with an optical field-based approach.
2Measurement precision
If radar is used to detect objects, then objects can be detected at a distance, but floating matters cannot be distinguished from other objects
Solution Approach 1:
The patent merges radar detection with optical image analysis. The radar is used to detect objects at a distance, while simultaneous optical images are captured and analyzed for brightness differences. By combining both detection methods, the system achieves both long-range detection capability and accurate floating matter identification.
Solution Approach 2:
The patent introduces optical images as an intermediary between radar detection and floating matter identification. The optical images serve as a mediator that provides additional information about the detected objects, allowing the system to distinguish floating matters from other objects through brightness comparison while maintaining the radar's long-range detection capability.
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
Enhances the accuracy of identifying floating matters by analyzing image differences and implementing appropriate vehicle controls, thereby improving safety and reducing unnecessary maneuvers.
Implementation Method 1
a radar 10, a camera 20
Implementation Method 2
irradiates a position in front of the host-vehicle with electromagnetic waves and detects an object in front of the host-vehicle based on reflected waves of the electromagnetic waves
Implementation Method 3
captures images of the position in front of the host-vehicle to acquire images
Implementation Method 4
The camera 20 focuses a light ray from a subject on a planar light-receiving surface of an image sensor element by means of a lens to form an image of the subject
Data Source
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AI summary
An object detection method includes irradiating a position in front of a host-vehicle with an electromagnetic wave, and detecting an object in front of the host-vehicle based on a reflected wave of the electromagnetic wave. The object detection method further includes capturing an image of the position in front of the host-vehicle to acquire an image, and determining whether the object is floating matters based on the acquired image if a state where the object is not detected changes to a state where the object is detected.