Camera Lens Abrasion Detection via Image Contrast Analysis
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Solution Overview
Problem
Automotive camera systems face performance degradation due to lens abrasions caused by mechanical cleaning, which affects image contrast and viewing performance, and there is a need for a standardized method to evaluate and detect this degradation effectively.
Innovation Solution
A system and method that captures images of a test object with defined light and dark portions, assigns shade values to pixels, determines mode values, calculates contrast differences, and normalizes these to assess camera performance degradation, triggering alerts when unacceptable degradation occurs, allowing for automatic notification and servicing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the lens is cleaned by wiping with finger, then the lens dirt is removed, but microscopic abrasions are created on the lens
Solution Approach 1:
The patent replaces manual mechanical wiping with an automated mechanical cleaning system that uses a cleaning element (such as a cloth or wiper) mounted on a robotic arm or automated mechanism. This system applies controlled mechanical forces through standardized motions (wiping, rubbing, or polishing) to remove dirt while minimizing lens damage through precise control of cleaning parameters.
2Object-affected harmful factors
If manual cleaning is performed repeatedly, then lens cleanliness is maintained, but image contrast and viewing performance degrade
Solution Approach 1:
The patent incorporates a feedback mechanism where image quality metrics (such as contrast, sharpness, or clarity) are continuously monitored after cleaning operations. This feedback is used to adjust cleaning parameters, frequency, and intensity to maintain optimal image quality while ensuring adequate lens cleanliness, preventing over-cleaning that would cause abrasion damage.
Solution Approach 2:
The patent employs parameter changes by varying cleaning forces, speeds, durations, and patterns based on detected lens condition and image quality requirements. The system dynamically adjusts these parameters to achieve effective dirt removal while maintaining image contrast and viewing performance within acceptable thresholds.
3Object-affected harmful factors
If lens cleaning frequency is increased, then lens dirt accumulation is prevented, but lens abrasion and performance degradation increase
Solution Approach 1:
The patent implements periodic cleaning actions based on detected dirt accumulation levels rather than fixed schedules. The system uses sensors to monitor lens contamination and triggers cleaning operations only when necessary, using periodic inspections to determine optimal cleaning timing and maintain lens durability while preventing excessive cleaning.
Solution Approach 2:
The patent applies preliminary protective measures by coating the lens with anti-stick or protective layers before cleaning operations. These coatings reduce the adhesion of dirt particles, allowing for less aggressive cleaning methods that remove contaminants more easily and reduce mechanical abrasion during subsequent cleaning cycles.
Data Source
AI summary
A method includes capturing a first image of an object at a first time using a camera and assigning shade values to a plurality of pixels in a portion of the first image. The object includes a light portion and a dark portion that is darker than the light portion. The method further includes identifying a first mode value of the shade values corresponding to the light portion of the object in the first image, and identifying a second mode value of the shade values corresponding to the dark portion of the object in the first image. The method further includes determining a difference between the first and second mode values, and determining a contrast of the first image based on the difference.