Multi-Camera White Balance Adjustment via Gray Pixel Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Intelligent surveillance systems face challenges in maintaining consistent color features across multiple cameras due to varying color temperatures caused by different white balance settings, which affects object matching and forensic searches.
Innovation Solution
A method and system that analyze images from multiple cameras to separate background and foreground pixels, identify gray pixels, adjust their colors to true gray, and unify the white balance across cameras with overlapping fields of view, using techniques like histogram analysis and mean color determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different white balance parameters are used in multiple cameras, then each camera can optimize its image quality for different lighting conditions, but the color consistency across cameras deteriorates
Solution Approach 1:
The patent changes the white balance parameters (specifically the blue and red gains) of cameras based on analysis of gray pixels in overlapping fields of view. By adjusting these parameters to make gray pixels appear truly gray across all cameras, the system achieves color consistency while maintaining adaptability to different lighting conditions through the automated parameter adjustment process.
2Ease of operation
If color gain adjustment is applied to each camera independently, then each camera can achieve optimal color balance for its specific conditions, but color matching between cameras becomes difficult
Solution Approach 1:
The system uses feedback from analyzing gray pixels in the overlapping fields of view to automatically adjust the white balance parameters of each camera. By measuring the actual color appearance of gray pixels and comparing it to the expected true gray color, the system generates corrective feedback that adjusts the blue and red gains to achieve consistent color representation across all cameras.
3Manufacturing precision
If manual white balance adjustment is performed for each camera, then color accuracy can be optimized, but the complexity and time required for system setup increases
Solution Approach 1:
The system performs self-service by automatically analyzing the overlapping fields of view between cameras, identifying gray pixels, and computing the necessary white balance parameter adjustments without requiring manual intervention. The cameras essentially adjust their own white balance settings based on the automated analysis of their shared field of view, eliminating the need for complex manual calibration procedures.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method of adjusting the color of images captured by a plurality of cameras comprises the steps of receiving a first image captured by a first camera from the plurality of cameras, analyzing the first image to separate the pixels in the first image into background pixels and foreground pixels, selecting pixels from the background pixels that have a color that is a shade of gray, determining the amount to adjust the colors of the selected pixels to move their colors towards true gray, and providing information for use in adjusting the color components of images from the plurality of cameras.