Optical Range Differentiator for Depth-Selective Autofocus
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Solution Overview
Problem
Existing auto-focusing systems struggle to accurately focus on specific features of interest in optical imaging systems, particularly when those features have different physical depths relative to other features, as they are influenced by shape and size rather than depth alone.
Innovation Solution
The system employs a range differentiator that includes an image generator, a depth differentiator, and a focus distance ascertainer to distinguish features at or above a predetermined threshold based on optical properties, using feature-specific illumination to create a depth-differentiated image, followed by focus scoring and adjustment to achieve precise auto-focusing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional auto-focusing systems are used, then the system can capture images of scenes, but it cannot accurately focus on specific features at different physical depths
Solution Approach 1:
The patent segments the image into multiple depth layers using a depth mask generated from stereo imaging. This segmentation allows the system to identify and focus on specific features at particular depths while ignoring features at other depths, thereby achieving accurate focus on features of interest despite variations in physical depth across the scene.
Solution Approach 2:
The patent applies local quality by using a depth mask that selectively identifies regions of interest at specific depths. The auto-focusing mechanism then applies focus adjustment locally to these identified regions rather than uniformly across the entire image, enabling precise depth-based focus control for specific features while maintaining other areas at their respective focus states.
2Measurement precision
If the system focuses on features at a specific depth, then focus accuracy for those features improves, but features at other depths become out of focus
Solution Approach 1:
The patent implements dynamic focus adjustment by continuously monitoring the depth mask and automatically modifying focus settings based on the identified depth of interest. This dynamic mechanism allows the system to adapt focus in real-time, ensuring that features at the target depth remain sharply focused while the system can switch between different depth planes as needed, preventing permanent information loss.
Solution Approach 2:
The system employs feedback through the depth mask analysis process, where the identified depth information feeds back to the auto-focusing mechanism. This feedback loop enables the system to continuously adjust focus based on the actual depth distribution in the scene, ensuring optimal focus on features of interest while maintaining the capability to capture information from multiple depth planes through the stereo imaging system.
3Measurement precision
If the system uses depth-based segmentation, then focus on specific depth features improves, but the complexity of image processing increases
Solution Approach 1:
The patent applies preliminary action by generating the depth mask from stereo imaging before the auto-focusing process begins. This pre-computed depth information is then used to guide the focus adjustment, eliminating the need for complex real-time depth calculation during focusing. The preliminary depth segmentation simplifies subsequent processing by providing ready-to-use depth region identifiers that directly inform focus decisions.
Data Source
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AI summary
A range differentiator useful for auto-focusing, the range differentiator including an image generator (540, 130, 132) providing an image of a scene at various physical depths, a depth differentiator (132) distinguishing portions of the image at depths below a predetermined threshold, irrespective of a shape of the portions, and providing a depth differentiated image and a focus distance ascertainer (132) ascertaining a focus distance based on the depth differentiated image.