Dual Lens Depth Map Analysis for Camera Blockage Detection
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Solution Overview
Problem
Existing safety surveillance systems rely on manual inspection to detect camera lens blockages or damage, leading to potential delays in identifying compromised camera functionality, which can compromise safety.
Innovation Solution
An image processing system with a dual lens module and processor that generates depth maps, calculates pixel depth mean and variance, and determines lens state by comparing these metrics to predefined thresholds, triggering an alarm if the lens is deemed abnormal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection is used to detect camera lens blockages, then device complexity is reduced, but detection speed and reliability deteriorate
Solution Approach 1:
The camera system performs self-diagnosis by using its own captured images to detect lens blockages. The processor analyzes depth map statistics (mean and variance) from images captured by the dual lens module to automatically determine lens state, eliminating the need for external manual inspection while maintaining high reliability
Solution Approach 2:
The system continuously monitors lens state by comparing depth map statistics against predefined thresholds and provides real-time feedback. When the pixel depth mean falls outside the distance range or variance exceeds thresholds, the system automatically triggers alarm signals to notify relevant personnel
2Speed
If automated lens state detection is implemented, then detection speed improves, but device complexity increases
Solution Approach 1:
The patent replaces manual mechanical inspection with automated digital image processing. The processor automatically generates depth maps from dual lens images, calculates pixel depth statistics, and compares them against thresholds to determine lens state, achieving rapid detection through computational methods rather than human observation
Solution Approach 2:
The system transforms image data into statistical parameters (pixel depth mean and variance) for easier analysis. By converting visual information into quantitative metrics that can be directly compared against predefined thresholds, the system achieves fast automated decision-making without complex processing
3Loss of time
If manual inspection is performed, then device complexity is minimized, but time loss increases
Solution Approach 1:
The system enables continuous monitoring of lens state by constantly capturing images, generating depth maps, and analyzing statistics. This continuous automated inspection eliminates downtime associated with manual checks, ensuring the camera remains operational and detecting blockages as they occur without interruption to surveillance operations
Data Source
AI summary
An image processing system includes a dual lens module and a processor. The dual lens module captures a pair of images. The processor generates a depth map of the pair of images. The processor generates a pixel depth distribution histogram according to the depth map. The processor calculates a pixel depth mean and a pixel depth variance according to the pixel depth distribution histogram. The processor determines whether the pixel depth mean is within a distance range and determines whether the pixel depth variance is smaller than a first threshold or larger than a second threshold, so as to determine that the dual lens module is situated in a normal state or an abnormal state.