Adaptive Pupil Detection Using Illuminance Lookup Table
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Solution Overview
Problem
Existing pupil detection technologies in vehicles lack accuracy due to the use of fixed threshold based binarization techniques that do not account for varying illuminance levels when capturing images.
Innovation Solution
A device and method utilizing an adaptive threshold based binarization technique, supported by a lookup table that correlates pupil sizes with illuminance levels, to improve pupil detection accuracy by adjusting the threshold based on measured illuminance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed threshold based binarization technique is used for pupil detection, then the device complexity is reduced, but the measurement precision of pupil detection deteriorates due to varying illuminance levels
Solution Approach 1:
The system performs preliminary measurement of illuminance levels before executing the pupil detection algorithm. By measuring the ambient illuminance in advance and using this information to adaptively adjust the binarization threshold, the system prepares the optimal detection parameters beforehand, thereby improving measurement precision without significantly increasing device complexity
Solution Approach 2:
The system dynamically changes the binarization threshold parameter based on measured illuminance levels. Instead of using a fixed threshold, the threshold is adjusted according to the actual lighting conditions, which resolves the contradiction by adapting the detection parameter to match environmental variations, thereby maintaining high measurement precision across different illuminance conditions
2Measurement precision
If an adaptive threshold based binarization technique with lookup table is used, then the measurement precision of pupil detection is improved, but the device complexity increases due to additional components
Solution Approach 1:
The lookup table is pre-computed and stored in advance, containing the relationship between illuminance levels and optimal binarization thresholds. During actual pupil detection, the system simply queries this pre-prepared table rather than performing complex real-time calculations, which improves measurement precision while minimizing the increase in device complexity
Solution Approach 2:
The lookup table acts as an intermediary between the illuminance measurement and the binarization process. Instead of directly implementing complex adaptive thresholding algorithms, the system uses the lookup table as a mediator that translates illuminance levels into appropriate thresholds, thereby simplifying the overall system structure while maintaining high measurement precision
3Measurement precision
If the threshold is dynamically adjusted based on illuminance, then the measurement precision is improved, but the loss of time increases due to additional measurement and adjustment steps
Solution Approach 1:
The lookup table is pre-computed and stored in advance, containing the relationship between illuminance levels and optimal binarization thresholds. During actual pupil detection, the system simply queries this pre-prepared table rather than performing complex real-time calculations, which improves measurement precision while minimizing the increase in device complexity
Solution Approach 2:
Instead of performing complex adaptive thresholding calculations in real-time, the system creates a simplified copy of the threshold-adjustment process by using a lookup table. This table stores pre-calculated threshold values that can be quickly retrieved, thereby maintaining measurement precision while significantly reducing the time loss associated with real-time computations
Data Source
AI summary
The present disclosure relates to a device for detecting a pupil taking account of illuminance and a method thereof, and provides a device for detecting a pupil taking account of illuminance capable of improving detection accuracy of the pupil by detecting a driver's pupil from an image using an adaptive threshold based binarization technique based on a lookup table in which sizes of the pupil corresponding to illuminance are written, and a method thereof.