Multi-Filter Object Alerting Under Variable Lighting Conditions
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Solution Overview
Problem
Existing warning devices struggle to accurately detect objects and issue appropriate warnings when it is difficult to determine the outside environment of a movable body, such as in varying weather conditions or when transitioning from bright to dark areas, leading to decreased image quality and reduced accuracy in object detection and warning issuance.
Innovation Solution
A warning device that acquires multiple images using different filter characteristics, performs object detection on each image, and issues warnings based on the consistency of object detection across these images, with higher-level warnings for consistent detections across all images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single filter is used for image acquisition, then the device complexity is reduced, but the image quality deteriorates under varying environmental conditions
Solution Approach 1:
The image acquisition system is segmented into multiple channels, each equipped with a different filter (first filter for daytime/visible light, second filter for nighttime/infrared light). This segmentation allows each filter to be optimized for specific environmental conditions, maintaining high image quality across varying conditions without requiring a single complex adaptive filter system.
Solution Approach 2:
The image acquisition device is designed with multi-functionality by incorporating both daytime and nighttime filters, enabling it to operate effectively in both daytime and nighttime conditions. This universal design allows the single device to adapt to different environmental conditions without requiring separate specialized devices.
2Manufacturing precision
If multiple filters are used for image acquisition, then the image quality is improved under varying environmental conditions, but the device complexity increases
Solution Approach 1:
The system dynamically switches between different filter configurations based on environmental conditions (daytime vs. nighttime). The filter selection is adapted in real-time according to the lighting conditions, allowing the device to maintain optimal image quality without requiring complex simultaneous multi-filter processing.
Solution Approach 2:
The filtering system is segmented into distinct daytime and nighttime filter channels, each handling specific wavelength ranges. This segmentation simplifies the overall system design by dividing the complex task of handling all lighting conditions into manageable, specialized sub-systems.
3Speed
If object detection is performed on a single image, then the processing speed is increased, but the detection accuracy decreases under challenging environmental conditions
Solution Approach 1:
The system merges detection results from multiple images acquired with different filters. By combining the detection outcomes from the first filter image and the second filter image, the system achieves more reliable object detection accuracy under varying environmental conditions while maintaining efficient processing through parallel acquisition.
Solution Approach 2:
The system uses feedback from detection results across multiple images to confirm object presence. When an object is detected in both the first filter image and the second filter image, the detection accuracy is enhanced through this cross-validation feedback mechanism, reducing false positives while maintaining processing efficiency.
4Loss of time
If warnings are issued based on single image detection, then the response time is reduced, but the reliability of warning issuance decreases
Solution Approach 1:
The warning issuance mechanism merges detection results from multiple images acquired with different filters. By combining these results, the system ensures that warnings are issued only when objects are consistently detected across different filtering conditions, significantly improving warning reliability without introducing substantial delays to the response time.
Solution Approach 2:
The system implements a feedback mechanism where detection results from multiple images are cross-validated before triggering a warning. This feedback loop confirms object presence across different environmental conditions, ensuring high warning reliability while maintaining timely response through efficient parallel processing.
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 object detection and warning issuance by utilizing multiple filter characteristics to improve image quality and consistency, ensuring appropriate warnings are issued even in challenging environmental conditions.
Implementation Method 1
An imaging device such as a digital camera generally takes an image of an area to be imaged by using a filter that transmits light with a specific wavelength
Data Source
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AI summary
To issue an appropriate warning based on detection of an object even under the circumstances where it is difficult to determine the outside environment of a movable body, a warning device (10) according to the present invention includes an image acquisition means (11) for acquiring a plurality of images respectively based on a plurality of filter characteristics, a detection means (12) for performing detection of a specified object on each of the plurality of acquired images, and a warning means (13) for issuing a specific warning when the object is detected from at least any one of the plurality of acquired images, wherein the warning means (13) issues a higher level of warning when the object is detected from all of the plurality of images than when the object is detected from some of the plurality of images.