Eye Image Exposure Control With Dynamic ROI Alignment
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Solution Overview
Problem
Existing image capture systems using slit lamps and digital cameras for eye examination often result in suboptimal image quality due to predefined Regions of Interest (ROIs) that do not align with the slit groove width, leading to discrepancies and potential saturation, which affects the diagnostic accuracy and treatment efficacy.
Innovation Solution
A dynamic optimization system that adjusts the ROI and target intensity values based on user-selected slit width and illumination intensity, utilizing a processor to calculate and adjust exposure settings dynamically, ensuring a predetermined percentage of pixels are below a target intensity level to optimize image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predefined Regions of Interest (ROIs) are used in digital cameras for eye examination, then the image capture process is simplified and faster, but the ROI does not align with the slit groove width leading to suboptimal image quality and potential saturation
Solution Approach 1:
The patent implements dynamic adjustment of ROI parameters based on real-time analysis of the captured image. The system calculates an intensity profile along the vertical centerline of the image, identifies the maximum slope point which corresponds to the slit groove edge, and dynamically repositions the ROI boundaries to align with the actual slit groove width. This dynamic adaptation resolves the contradiction by maintaining fast capture (predefined ROI) while achieving precise alignment (optimal image quality) through real-time parameter adjustment.
Solution Approach 2:
The system changes the ROI parameters (position and width) based on the calculated intensity profile characteristics. By identifying the maximum slope point in the intensity profile and using it to determine the optimal ROI boundaries, the system adapts the ROI parameters to match the actual slit groove dimensions in each captured image, thereby resolving the misalignment issue while maintaining efficient capture.
2Illumination intensity
If exposure settings are increased to improve image brightness, then darker regions become more visible, but saturation occurs in brighter regions reducing diagnostic accuracy
Solution Approach 1:
The patent applies different intensity optimization strategies to different regions within the ROI. By analyzing the intensity profile and identifying regions with different brightness characteristics, the system can apply localized adjustments to ensure that both dark and bright regions are optimally exposed without causing saturation. This local quality approach allows differential treatment of different image regions to achieve overall optimal diagnostic quality.
Data Source
AI summary
A system and method for dynamically optimizing an eye image, comprising an imaging unit with a predetermined target intensity value, a memory, and at least one processor executing computer-readable code. The processor receives an eye image from the imaging unit and calculates an intensity profile along a region of interest (ROI). A maximum intensity point, representing the ROI center, and a maximum slope of the profile are identified. A symmetric profile is generated by mirroring the portion containing the maximum slope around the maximum intensity point. An optimized ROI is determined from the symmetric profile, and a grey level histogram is generated. A Cumulative Distribution Function (CDF) is calculated from the histogram. A predetermined percentage of pixels in the optimized ROI is set to be lower than an optimized target intensity value. Based on the CDF, the optimized target intensity value is calculated, and the imaging unit adjusts accordingly.