Image Disparity Focus Selection for Multi-Sensor Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional imaging systems with variable focus lenses are bulky, slow, and vulnerable to environmental impacts, limiting their operability and ability to adapt to different imaging conditions.
Innovation Solution
Implementing a multi-image sensor system that utilizes image disparity to automatically select focus by capturing images with multiple sensors, determining characteristic differences, and adjusting focus positions based on calculated distances to improve focus selection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional variable focus lenses are used, then focus adjustment capability is provided, but the system becomes bulky and slow
Solution Approach 1:
The patent divides the imaging system into multiple static image sensors, each optimized for specific focus ranges. Instead of using a single lens with variable focus capability, the system segments the focus adjustment function across multiple fixed-focus sensors, eliminating the need for bulky mechanical focus adjustment mechanisms.
Solution Approach 2:
The patent replaces the mechanical variable focus lens system with a computational approach using multiple static image sensors. The focus selection is determined through image processing and disparity analysis rather than physical lens movement, thereby eliminating mechanical complexity and reducing system size.
2Adaptability or versatility
If conventional variable focus lenses are used, then focus adjustment capability is provided, but the system becomes slow and vulnerable to environmental impacts
Solution Approach 1:
The patent captures images from multiple image sensors simultaneously at different focus positions before the actual measurement or processing is needed. This preliminary capture of multiple focus states allows the system to quickly select and process the appropriate image without waiting for slow mechanical focus adjustment during the measurement process.
Solution Approach 2:
The patent substitutes mechanical focus adjustment with a computational selection process. By using multiple static sensors to capture images at different focus positions simultaneously and then selecting the appropriate image through computational analysis, the system achieves fast focus selection without the speed limitations of mechanical lens movement.
3Speed
If multiple image sensors are used for automatic focus selection, then focus selection speed is enhanced, but device complexity increases
Solution Approach 1:
The patent designs the multiple image sensors to serve multiple functions: they not only capture images for focus selection but also provide depth information through disparity analysis. This multi-functionality allows the system to achieve fast focus selection while using the same sensors for additional processing tasks, thereby reducing overall system complexity.
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes image disparity between multiple sensors to determine focus status. This intermediary computational layer simplifies the control logic by providing a clear decision metric (disparity-based focus determination) that automatically selects the appropriate image sensor and focus position without complex control algorithms.
4Measurement precision
If focus adjustments are made frequently, then imaging accuracy is maintained, but power consumption increases
Solution Approach 1:
The patent performs preliminary image capture from multiple focus positions simultaneously, so that when focus adjustment is needed, the system can immediately select from pre-captured images rather than performing time-consuming and energy-intensive mechanical focus adjustments. This preliminary action maintains imaging accuracy while minimizing power consumption during actual measurement operations.
Solution Approach 2:
The patent replaces energy-intensive mechanical focus adjustments with a low-power computational selection process. By using multiple static sensors to capture images at different focus positions and then selecting the appropriate image through disparity analysis, the system maintains imaging accuracy without the continuous power consumption associated with active mechanical focus control.
Data Source
AI summary
Embodiments of the disclosure relate generally to automatic focus selection in a multi-imager environment. Embodiments include methods, systems, and apparatuses configured for capturing by a first image sensor, a first image of a visual object with a background associated with a subject. A characteristic difference between the visual object in the first image and the background in the first image is determined and a distance determination mode is selected based on the determined characteristic difference. Accordingly, a distance to the subject is calculated based on the selected distance determination mode and a second image sensor is controlled to capture a second image of the subject, based on the calculated distance to the subject.