Camera Bright Light Pixel Adjustment for False Alarm Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current analytics software in security cameras cannot differentiate between changes caused by lighting or environmental conditions and real threats, leading to false alarms, especially at night or in areas with high vehicular traffic, which can result in the cameras being turned off.
Innovation Solution
A method that adjusts pixel values in captured images to account for bright lights by forming two-dimensional arrays, measuring average and standard deviation, and mathematically adjusting pixels associated with lighting changes, allowing for discrimination between lighting changes and potential threats before further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image differencing and change detection analytics are used to detect threats, then threat detection capability is improved, but false alarms increase due to lighting changes
Solution Approach 1:
The patent segments the image processing into distinct stages: capturing a reference image, capturing a current image, adjusting pixel values in both images, and then performing differencing. This segmentation allows lighting-related pixel adjustments to be applied before comparison, separating the lighting normalization function from the threat detection function.
Solution Approach 2:
The patent applies preliminary action by adjusting pixel values in both the reference and current images before performing image differencing. The pixel adjustment process normalizes lighting conditions in advance, so that subsequent differencing operations compare only meaningful changes (potential threats) rather than being confounded by lighting variations.
2Area of stationary object
If cameras monitor areas with high vehicular traffic at night, then surveillance coverage is improved, but false alarms increase due to vehicle headlights
Solution Approach 1:
The patent converts the harmful effect of bright lights (vehicle headlights) into a beneficial process by using the pixel adjustment algorithm to normalize their impact. Instead of allowing headlights to cause false alarms, the system adjusts pixel values to account for these bright light sources, transforming a problem into part of the solution.
3Measurement precision
If analytics software detects all changes in the field-of-view, then detection sensitivity is improved, but discrimination between lighting changes and real threats deteriorates
Solution Approach 1:
The patent applies local quality by adjusting pixel values based on local characteristics of the image data. The pixel adjustment process considers the specific values and distributions in different regions of the reference and current images, applying localized normalization that preserves genuine changes while correcting lighting-related variations.
Data Source
AI summary
The present disclosure describes how to reduce or eliminate negative effects caused by bright lights in a change detection system. As a result, false alarms caused by lighting changes may be significantly reduced or eliminated.