Facial Recognition Illumination Control for Reflection Reduction
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Solution Overview
Problem
Face authentication accuracy is affected by varying light conditions and reflections from glasses or masks, leading to decreased accuracy in identifying facial features.
Innovation Solution
A face authentication apparatus that generates and projects customized image data to control light on a subject's face, adjusting brightness and color to reduce reflections and ensure uniform illumination, using a camera and projector system to capture and project images dynamically based on real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If illumination light is applied to illuminate the subject, then the captured image brightness is improved, but light reflections from glasses or masks increase causing decreased authentication accuracy
Solution Approach 1:
The patent applies different illumination intensities to different regions of the subject's face. The control unit adjusts the illumination light intensity based on the captured image, reducing intensity in regions where reflections are detected (such as areas with glasses or masks) while maintaining or increasing intensity in other regions. This localized quality adjustment resolves the contradiction by ensuring sufficient overall brightness while minimizing reflection-induced accuracy degradation in specific critical areas.
Solution Approach 2:
The patent dynamically changes the illumination light parameters (intensity, and potentially color temperature) based on real-time analysis of the captured image. The control unit modifies these parameters to optimize the balance between image brightness and reflection minimization, thereby improving authentication accuracy without sacrificing necessary illumination levels.
2Illumination intensity
If illumination light intensity is increased to improve image capture, then brightness is improved, but glare and reflections increase reducing measurement precision
Solution Approach 1:
The system applies non-uniform illumination by adjusting light intensity locally across different facial regions. Areas prone to reflections (such as areas with glasses or masks) receive reduced illumination intensity, while other areas maintain higher intensity for adequate brightness. This localized approach preserves measurement precision of facial features while ensuring sufficient overall image brightness.
Solution Approach 2:
The control unit continuously monitors the captured image for reflections and glare, then adjusts the illumination light intensity accordingly. This feedback mechanism allows the system to dynamically optimize the balance between brightness and measurement precision, reducing glare in real-time while maintaining adequate illumination for accurate facial feature identification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves authentication accuracy by minimizing light reflections and ensuring consistent brightness, enhancing the reliability of facial recognition even with glasses or masks, and maintaining accuracy across different lighting conditions.
Implementation Method 1
a projection image data transmitter that transmits the projection image data to a projector configured to project the projection image onto the subject
Implementation Method 2
an image data receiver that receives image data including a captured image of a subject from a camera
Data Source
AI summary
A facial recognition device includes: an image data receiving unit that receives image data showing an object from a camera; an image generation unit that generates projection image data of a projection image projected onto the object according to the image data; a projection image data transmission unit that transmits the projection image data to a projector for projecting the projection image onto the object; a projected object image data receiving unit that receives, from the camera, projected object image data of the object on which the projection image is projected; and a facial recognition unit that performs facial recognition processing of the object according to the projected object image data.