Iris Imaging Test Chart for Recognition Setting Calibration
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Solution Overview
Problem
Existing imaging test charts are inadequate for accurately adjusting imaging environments and settings for iris recognition, making it difficult to acquire suitable images for iris recognition.
Innovation Solution
An imaging test chart and information processing apparatus that includes an iris pattern for evaluating imaging environments and settings, with a system for creating, acquiring, and analyzing chart images to optimize these factors for iris recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing imaging test charts are used, then general imaging characteristics can be evaluated, but iris recognition-specific imaging environments and settings cannot be accurately adjusted
Solution Approach 1:
The test chart is segmented into multiple independent evaluation regions, each targeting a specific imaging parameter (focus, exposure, color, contrast). This allows separate optimization of each parameter for iris recognition without compromising others, resolving the contradiction between reliability and adaptability.
Solution Approach 2:
Different regions of the test chart are designed with specific local characteristics (e.g., high-contrast patterns for focus evaluation, color-specific blocks for color accuracy). This enables tailored evaluation of imaging qualities critical for iris recognition while maintaining overall chart functionality.
2Reliability
If imaging settings are adjusted to optimize iris recognition, then recognition accuracy improves, but the complexity of setting adjustment increases
Solution Approach 1:
The test chart provides visual feedback for each imaging parameter through dedicated evaluation regions. Users can directly observe the impact of setting adjustments on image quality and iteratively optimize parameters, reducing the complexity of setting adjustment while improving recognition accuracy.
Solution Approach 2:
The test chart is designed in advance with specific patterns and structures that pre-evaluate imaging qualities. This preliminary setup allows users to quickly assess and adjust settings without complex analysis, simplifying the optimization process while maintaining high accuracy.
3Measurement precision
If a comprehensive test chart for all imaging parameters is created, then evaluation completeness improves, but the chart complexity and creation difficulty increase
Solution Approach 1:
The comprehensive evaluation is achieved through segmentation into independent parameter-specific regions. Each region evaluates a single parameter using optimized patterns, allowing complete evaluation without creating a single complex structure. This modular approach reduces overall chart complexity while maintaining measurement precision.
Solution Approach 2:
The test chart design incorporates universal principles that can evaluate multiple parameters through a single structured framework. The same basic pattern design language is used across all parameter evaluations, reducing creation difficulty while maintaining comprehensive coverage of imaging qualities.
Data Source
AI summary
An imaging test chart (100) includes an iris pattern IRP for evaluating at least one of an imaging environment and an imaging setting.