Camera Lens Accumulation Detection for Vehicle Obstacle Recognition
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Solution Overview
Problem
The stability of obstacle detection processing in vehicle-mounted devices is affected by light source environments and background changes, leading to unstable detection results due to accumulation on camera lenses, causing suspension and resumption of detection processing to also be unstable.
Innovation Solution
A surrounding environment recognition device with an accumulation detection unit that identifies and manages accumulations on camera lenses, a tracking unit for maintaining visibility, and a decision-making system for suspending and resuming object detection processing based on lens conditions and tracking success.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If obstacle detection processing is suspended and resumed based on accumulation detection results, then detection stability can be improved, but the processing becomes unstable due to affected by light source environment and background changes
Solution Approach 1:
The patent segments the image processing into distinct functional modules: accumulation detection unit that identifies lens accumulations, tracking unit that monitors specific image features, and decision-making system that determines suspend/resume actions. This segmentation allows each module to focus on a specific aspect, improving overall system reliability while making the complex processing more manageable and stable.
Solution Approach 2:
The patent implements feedback mechanisms where the accumulation detection unit continuously monitors lens conditions and provides information to the decision-making system, which adjusts detection processing accordingly. The tracking unit also provides feedback on image feature stability, creating a closed-loop system that adapts to changing conditions and maintains stable detection performance despite environmental variations.
2Reliability
If accumulation detection is performed to improve detection stability, then obstacle detection reliability improves, but the system complexity increases
Solution Approach 1:
The patent merges the accumulation detection functionality with the existing obstacle detection system, allowing the same image processing pipeline to serve dual purposes. The accumulation detection unit utilizes the photographic images already being captured for obstacle detection, combining these functions to improve reliability without proportionally increasing system complexity.
Solution Approach 2:
The decision-making system serves multiple functions: it determines when to suspend obstacle detection based on accumulation detection results, manages the suspend/resume processing, and maintains overall system coordination. This multi-functionality reduces the need for separate dedicated components, thereby improving detection reliability while limiting the increase in system complexity.
Data Source
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AI summary
A surrounding environment recognition device includes: an image acquisition unit that obtains a photographic image from a camera for capturing, via a camera lens, an image of a surrounding environment around a mobile object; an image recognition unit that recognizes an object image of an object present in the surrounding environment based upon the photographic image obtained by the image acquisition unit; an accumulation detection unit that detects accumulation settled on the camera lens based upon the photographic image obtained by the image acquisition unit; a suspension decision-making unit that makes a decision, based upon detection results provided by the accumulation detection unit, whether or not to suspend operation of the image recognition unit; a tracking unit that detects a characteristic quantity in a tracking target image from a specific area in an image captured by the image acquisition unit for a reference frame, determines through calculation an estimated area where the characteristic quantity should be detected in an image captured by the image acquisition unit for a later frame relative to the reference frame and makes a decision as to whether or not the characteristic quantity for the tracking target image is also present in the estimated area; and a resumption decision-making unit that makes a decision, based upon at least decision-making results provided by the tracking unit and indicating whether or not the characteristic quantity for the tracking target image is present, as to whether or not to resume the operation of the image recognition unit currently in a suspended state.