Time-of-flight sensor iris capture system
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Solution Overview
Problem
Current iris capture systems face limitations in operational range, accuracy, and user mobility, with limited depth of field and inaccurate depth information, leading to difficulties in capturing clear iris images without requiring users to remain still for extended periods.
Innovation Solution
A system combining a commercial off-the-shelf high-resolution camera with near-infrared illumination and a time-of-flight (TOF) depth sensor to accurately determine the 3D shape of a face, allowing for quick focus calculation and deblurring of iris images, even when subjects are moving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple synchronized high-speed video cameras are used for iris capture, then throughput is improved, but depth of field remains limited
Solution Approach 1:
The system segments the depth measurement function from the image capture function by using a dedicated TOF sensor for depth measurement while separate cameras capture iris images. This allows independent optimization of depth measurement accuracy and image quality without being constrained by the depth of field limitations of traditional single-camera systems.
Solution Approach 2:
The TOF sensor acts as an intermediary that provides accurate depth information to the autofocus system, enabling the camera to automatically adjust focus based on measured subject distance. This intermediary depth measurement capability resolves the contradiction by providing the information needed to dynamically optimize focus while maintaining high throughput.
2Adaptability or versatility
If stereo vision is used to compute depth information, then operational range is extended, but measurement accuracy deteriorates
Solution Approach 1:
The system replaces the optical-mechanical stereo vision approach with a time-of-flight sensing mechanism that measures depth by timing the round-trip travel of light. This substitution provides direct, accurate depth measurements independent of baseline length, resolving the trade-off between operational range and measurement accuracy.
Solution Approach 2:
The system changes the measurement parameter from spatial disparity (in stereo vision) to time of flight. By measuring the time for light to travel to and from the subject, the system achieves accurate depth measurement without being constrained by baseline length, thereby extending operational range while maintaining precision.
3Speed
If high shutter speed cameras are used, then capturing speed is improved, but users must remain still for extended periods
Solution Approach 1:
The system performs preliminary depth measurement using the TOF sensor before image capture to pre-determine the subject distance. This preliminary action enables the autofocus system to be pre-positioned, eliminating the need for users to remain still during the capture process and reducing the required stationary time while maintaining high capturing speed.
Solution Approach 2:
The system uses feedback from the TOF sensor's continuous depth measurement to dynamically adjust focus in real-time. This feedback mechanism allows the system to track moving subjects automatically, enabling high-speed capture without requiring users to remain still, as the focus adjusts continuously based on measured subject position.
4Measurement precision
If longer baseline is used in stereo vision, then depth measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The system extracts the depth measurement function from the complex stereo vision system and implements it using a dedicated TOF sensor. This extraction eliminates the need for long baselines and complex multi-camera rig configurations, achieving accurate depth measurement with a simpler, more compact device architecture.
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
The system achieves an extended depth of field, enlarged capture volume, and improved capturing speed, enabling accurate and fast iris capture with reduced system delay, suitable for compact and portable security applications.
Implementation Method 1
a time-of-flight (TOF) depth sensor
Data Source
AI summary
A method of identifying a living being includes using a time-of-flight sensor to determine a location of a face of the living being. An image of an iris of the living being is produced dependent upon the location of the face as determined by the time-of-flight sensor. The produced image is processed to determine an identity of the living being.