Vehicle Image Warning Integration for AVM Blind Spot Detection
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Solution Overview
Problem
Current Around View Monitor (AVM) systems suffer from image stitching errors, particularly in large vehicles, leading to blind spots and potential accidents due to software and hardware limitations in image processing, which are not adequately addressed by existing technologies.
Innovation Solution
An image integrated warning system that combines radar sensing with image identification to provide early warnings of obstacles' direction and distance on a real image, using camera units, sensing units, a processing unit, and a display unit to create a virtual alert range with color-coded sections indicating hazard levels and triggering audio warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If AVM systems use image stitching to create aerial view images, then blind spots during reversing or turning can be reduced, but image stitching errors cause overlapped or disappeared images leading to system errors
Solution Approach 1:
The patent introduces radar sensing units as an intermediary technology to detect obstacles and provide distance information. This mediator compensates for the reliability deficiencies of image stitching by providing independent obstacle detection data that can verify or supplement the visual information from stitched images.
Solution Approach 2:
The patent merges radar sensing technology with AVM image stitching technology into an integrated warning system. By combining the obstacle detection capabilities of radar with the visual representation of image stitching, the system achieves both comprehensive coverage and high reliability in obstacle identification.
2Area of stationary object
If AVM systems are applied to large vehicles, then comprehensive surrounding monitoring is achieved, but numerous blind spots remain hidden from direct visual observation causing safety hazards
Solution Approach 1:
The patent segments the vehicle surrounding space into multiple monitoring zones using multiple camera units positioned at different locations. Each camera captures a specific sector, and the image stitching module integrates these segments into a comprehensive aerial view that eliminates blind spots across the entire vehicle perimeter.
Solution Approach 2:
The patent transitions from two-dimensional direct visual observation to three-dimensional aerial view representation. By processing images from multiple cameras into a top-down aerial perspective, the system reveals spatial relationships and obstacles that are invisible from the driver's ground-level viewpoint, effectively eliminating blind spots.
3Measurement precision
If image identification module tracks and compares vehicle surrounding images, then obstacle identification is achieved, but system complexity increases due to integration of multiple sensing and processing components
Solution Approach 1:
The patent designs the processing unit to perform multiple functions: image stitching from camera inputs, obstacle identification through tracking and comparison, radar data processing, and integrated warning generation. This multi-functional approach consolidates what could be separate complex systems into a single integrated unit, managing complexity through functional consolidation.
Solution Approach 2:
The image identification module continuously tracks and compares vehicle surrounding images over time, creating a feedback mechanism that improves obstacle detection accuracy. By comparing current frames with previous frames and tracking obstacle movement, the system achieves high measurement precision while managing complexity through iterative refinement rather than requiring overly complex instantaneous analysis.
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
The system effectively compensates for image stitching errors by providing precise blind spot scanning and visualization of obstacles' locations, enhancing driver awareness and safety by integrating radar sensing with image processing to prevent accidents.
Implementation Method 1
a plurality of sensing units (20)... to transmit sensing waves toward the real image stitching directions and to output sensing messages based on return waves
Data Source
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AI summary
An image integrated warning system for a vehicle, includes the component of a camera unit, a sensing unit, an image stitching module, an image identification module, an image integration module and a display unit etc. A predefined virtual alert range is integrated into a vehicle surrounding real image, and an approaching obstacle is indicated in a warning section according to an identification message of an image identification and a sensing message of a sensing unit, thereby allowing the driver to understand the location and distance of the obstacle relative to the vehicle from the image directly. Consequently, the effects of safe warning, facilitated determination and observation for the driver can be achieved.