Vision Assistance System Dynamic Image Adjustment
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Solution Overview
Problem
Current assistive technologies for vision impairment lack portability, customizability, and affordability, failing to effectively enhance viewability for individuals with varying visual challenges.
Innovation Solution
A system and method for dynamic and customizable image adjustment using a camera system, processor, and user interface, which applies image adjustments such as inversion, contrast, exposure, and color overlay based on user interactions or machine learning recommendations, enabling enhanced viewability through a user device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current assistive technologies are used, then vision assistance is provided, but portability, customizability, and affordability are insufficient
Solution Approach 1:
The system integrates multiple functions into a single device: image capture via camera system, real-time processing through neural processing unit, multiple adjustment modes (user-defined, AI-recommended, preset), and various display options. This multi-functional integration improves adaptability while managing complexity through unified architecture.
Solution Approach 2:
The system dynamically adjusts image parameters in real-time based on user interactions, environmental conditions, and AI recommendations. The adjustment pipeline continuously processes images and applies modifications (inversion, contrast, exposure, color overlay) dynamically, allowing the device to adapt to changing visual needs and environments.
2Reliability
If multiple image adjustments are applied, then viewability is enhanced, but processing time and computational resources increase
Solution Approach 1:
The system pre-calculates and prepares multiple adjustment options before presenting them to the user. AI recommendations are generated in advance based on environmental analysis, and preset adjustments are pre-configured for common scenarios. This preliminary processing reduces real-time decision latency while maintaining viewability enhancement.
Solution Approach 2:
The system applies adjustments selectively based on the specific visual needs and environmental conditions. Not all adjustment types are applied simultaneously - only those relevant to the current situation are processed. This partial action approach maintains viewability enhancement while reducing unnecessary computational overhead and processing time.
3Ease of operation
If real-time image adjustment is implemented, then user independence is improved, but device complexity and cost increase
Solution Approach 1:
The system enables users to independently adjust image parameters through intuitive controls and AI-assisted recommendations. Users can select from multiple adjustment modes (manual control, AI recommendations, presets) and make real-time modifications without assistance. This self-service capability improves user independence while the standardized hardware platform manages manufacturing complexity.
Data Source
AI summary
Disclosed are methods, systems and non-transitory computer readable memory for dynamic image adjustment and augmentation for enhancement of viewability. For instance, a method may include obtaining, from a camera system, at least one image of a visual environment or situation, wherein a first image of the at least one image includes a first set of pixels; implementing, in accordance with an adjustment layer, one or more image adjustments to the first set of pixels to obtain an augmented set of pixels, wherein the adjustment layer is determined (a) through a user interface by user interactions from a user and/or (b) a recommendation of a machine learning model; and presenting, on at least one display, the augmented set of pixels to the user.