A Computer Vision Sensor for Efficient Real-Time Object Detection Under Varying Lighting Conditions
Technology Overview
This technology introduces a new vision sensor capable of detecting objects under varying lighting conditions, achieving more robust real-time object detection. It is designed to remain unaffected by sudden lighting changes, making it suitable for applications like surveillance cameras and self-navigating vehicles.
CATEGORY
Vessel Performance & Navigation 
Autonomy & Sensing 
Safety, Monitoring & Risk Reduction TECHNOLOGY READINESS LEVEL (TRL)
Lighting-Resilient Vision Sensor Technology
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Lighting-Invariant Object Detection:
Maintains consistent signal output despite light changes. Prevents detection errors caused by sudden brightness shifts. Ensures reliable real-time object recognition
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Reduced AI Training Requirements:
Requires smaller training datasets. Uses less memory and computation. Lowers hardware and operational costs
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More Robust Computer Vision:
Improves DNN detection accuracy in unseen lighting conditions. Eliminates need for complex pre-processing. Enhances real-world deployment reliability
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Wide Application Potential:
Surveillance systems, autonomous and self-navigating vehicles, outdoor monitoring under changing weather
Maritime Use Cases
The computer vision sensor could be used for enhanced maritime surveillance and security, enabling the automatic detection and tracking of vessels, small boats, or other objects of interest in coastal or offshore areas.
The sensor could also support search and rescue operations by rapidly identifying and locating people or objects in the water, improving response times and effectiveness.
The real-time object detection capabilities could be integrated into autonomous or remotely operated maritime vehicles, such as USVs or ROVs, to enhance their situational awareness and collision avoidance abilities.
