Image Capture Illumination Sequencing for Motion-Error ALC
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Solution Overview
Problem
Images captured by a camera often introduce errors due to movement of the object between frames when ambient light correction is applied, making accurate comparison or color determination challenging.
Innovation Solution
A method involving capturing a plurality of primary images with varying controlled illumination, performing ambient light correction on subsets of these images to generate ALC images, calculating error values for pairs of ALC images, and selecting the image with the lowest error to minimize motion-induced errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ambient light correction is applied by comparing pixels of captured images, then color accuracy is improved, but motion errors increase when the object moves between frames
Solution Approach 1:
The system performs preliminary actions by capturing multiple images with varying controlled illumination before the final comparison. By capturing a sequence of images with different illumination states (ambient light only, ambient light plus controlled light, ambient light plus controlled light at different intensities), the system prepares multiple candidates for ambient light correction, ensuring that at least one image pair has minimal motion error even if the object moves during capture
Solution Approach 2:
The system changes illumination parameters by varying the controlled light source intensity and state across multiple captured images. By capturing images with different illumination conditions (different ratios of ambient to controlled light), the system creates multiple versions of the same scene that can be compared to determine which has the minimum motion error, thereby resolving the contradiction between color accuracy and motion error
2Reliability
If multiple images are captured with varying illumination to reduce motion error, then motion error is minimized, but processing complexity increases
Solution Approach 1:
The system uses parameter changes in illumination as a systematic approach to generate multiple images with different controlled light intensities. This structured variation allows the processor to efficiently compare images based on known illumination differences, reducing the computational complexity of determining which image has minimum motion error compared to analyzing arbitrary multiple images
3Reliability
If multiple images are captured with varying illumination over time, then motion-induced errors are reduced, but capture time increases
Solution Approach 1:
The system employs periodic action by capturing images in a structured sequence with controlled illumination variations. Instead of capturing multiple random images over an extended period, the system uses periodic illumination changes (switching between ambient light only and ambient light plus controlled light at different intensities) to efficiently capture the necessary data in minimal time, reducing the time loss while still minimizing motion-induced errors
Data Source
AI summary
According to an aspect, there is provided a method for minimising error in ambient light corrected (ALC) images due to motion. The method comprises capturing a plurality of primary images of an object over a time window, with controlled illumination of the object varying over time, performing ambient light correction on at least a portion of the plurality of primary images to generate a plurality of ambient light corrected images, each ALC image being generated based on demodulating a sub-set of the plurality of primary images with differing controlled illumination, calculating an error value for pairs of ALC images, each pair of ALC images including a first ALC image and a second ALC image and comparing the error values for each pair of ALC images and selecting an error-minimised image from the pair of ALC images having the lowest error value within the time window Calculating the error value comprises comparing each pixel of the first ALC image with a corresponding pixel of the second ALC image, and determining a change in intensity for each pixel between the first ALC image and the second ALC image, and calculating an error value for the pair of ALC images based on the change in intensity over a plurality of pixels.