Adaptive Reading Machine Mode Processing for Visually Impaired
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Solution Overview
Problem
Existing reading machines for visually impaired individuals lack the ability to adapt to different contexts and efficiently process specific types of visual information, such as menus, documents, clothing, and navigation, due to limited mode flexibility and processing efficiency.
Innovation Solution
A computer program product that allows a reading machine to operate in various modes by receiving data specifying the mode, accessing a knowledge base to configure settings, and processing images to identify target visual elements, such as elaborate fonts, clothing patterns, or navigation elements, optimizing performance for specific uses like restaurant, document, outdoor, or indoor environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a reading machine uses a single processing mode for all images, then the device complexity is reduced, but the adaptability to different contexts (menus, documents, clothing, navigation) deteriorates
Solution Approach 1:
The reading machine implements dynamic mode selection by automatically detecting image characteristics (text density, font size, color patterns, geometric shapes) and switching between different processing modes (document mode, menu mode, clothing mode, navigation mode) based on the detected scene type, allowing the system to adapt its processing parameters in real-time
Solution Approach 2:
The system changes processing parameters dynamically by adjusting OCR sensitivity, color thresholding values, pattern recognition algorithms, and feature extraction methods according to the detected mode, optimizing performance for each specific context without requiring separate dedicated devices
2Ease of operation
If a reading machine processes all images using general-purpose algorithms, then the ease of operation is maintained, but the measurement precision of specific visual elements (elaborate fonts, clothing patterns, navigation elements) deteriorates
Solution Approach 1:
The reading machine performs self-service by automatically analyzing image characteristics and selecting appropriate processing modes without user intervention, using built-in detection algorithms to identify text regions, patterns, and geometric features that indicate the appropriate mode for processing
Solution Approach 2:
The system performs preliminary analysis of the captured image to detect scene characteristics (font elaboration, pattern complexity, geometric shapes) before applying the main processing algorithm, allowing it to pre-configured the appropriate processing mode and parameters for optimal precision
3Productivity
If a reading machine uses mode-specific processing algorithms, then the productivity for specific tasks is improved, but the device complexity increases
Solution Approach 1:
The reading machine achieves multi-functionality by incorporating a single device that can operate in multiple modes (document reading, menu analysis, clothing pattern recognition, navigation assistance) through software-based mode switching, eliminating the need for separate specialized devices while maintaining high processing efficiency for each task type
Data Source
AI summary
A reading machine that operates in various modes includes image correction processing is described. The reading machine operates in different modes that optimize performance for specific uses of the reading machine. The reading machine receives data that specifies a mode to use for processing an image. The reading machine accesses a knowledge base to provide data to the machine for the specified mode, with the data including specific target visual elements that are expected to be encountered in processing images for the specified mode. The reading machine captures one or several images and processes the one or several images to identify one or more of the target elements in the image using information obtained from the knowledge base.