Iris Recognition Impairment Filtering via Gaze Motion Compensation
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Solution Overview
Problem
Iris recognition systems face inaccuracies and false authentication due to impairment data in captured images caused by interference such as image sensor imperfections, scratches, and interfering light, leading to less accurate detection and extraction of iris features.
Innovation Solution
The method involves capturing multiple iris images while the user changes gaze, allowing the system to detect and filter out impairment data by compensating for gaze motion, either by disregarding fixed-position data or using averaging, majority voting, or selecting median/mean feature patterns to isolate iris features from moving interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple iris images are captured and processed to remove impairment data, then the reliability and accuracy of iris recognition is improved, but the complexity of the system increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple iris images before final recognition. By acquiring several images with different gaze directions in advance, the system enables subsequent impairment detection and removal processes, improving reliability without requiring complex real-time processing during authentication
Solution Approach 2:
The patent segments the iris recognition process into distinct stages: image capture, impairment detection, impairment removal, and feature extraction. By dividing the overall process into manageable segments, the system handles complexity in an organized manner while maintaining high reliability through systematic processing of multiple images
2Measurement precision
If gaze motion compensation is applied to fix the iris position, then the accuracy of feature detection is improved, but the processing time increases
Solution Approach 1:
Gaze motion compensation is performed as a preliminary step before feature detection. By pre-aligning multiple iris images to a common reference position, the system enables accurate feature detection without requiring complex real-time processing, thus improving measurement precision while managing processing time efficiently
Solution Approach 2:
The system creates a reference iris image that serves as a template for aligning subsequent images. By copying and using this reference image for gaze motion compensation, the system achieves accurate feature detection without requiring complex computational processes for each individual image
Data Source
AI summary
An iris recognition system and method configured to reduce impact of impairment data in captured iris images. The system comprises a camera configured to capture first and second images of a user's iris. A processing unit of the system is configured to cause the user to change gaze between the capturing of the first and second images, create a representation of each of the first and second iris images, where each spatial sample of an image sensor of the camera capturing the iris images is gaze-motion compensated to correspond to a same position on the iris for the sequentially captured first and second iris images, thereby causing the iris to be fixed in the representations while any impairment data will move with the change in gaze of the user, and to filter the moving impairment data from at least one of the representations of the first and second iris images.