Image Legibility Assessment Using Text Component Analysis
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Solution Overview
Problem
The proliferation of digital content items has led to issues with image legibility, particularly when images are downsized for various electronic devices, as textual information may become illegible, affecting user experience and content availability.
Innovation Solution
A system and method for assessing image legibility using connected component analysis and trained classifiers to identify and evaluate text components within images, determining the legibility of text and overall images, and providing a confidence level for automatic assessment, enabling automatic determination of image legibility without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are downsized for various electronic devices, then adaptability to different devices is improved, but text legibility deteriorates
Solution Approach 1:
The system performs preliminary assessment of image legibility before distribution to electronic devices. By evaluating text components, connected components, and overall image quality in advance, the system identifies illegible images before they reach devices, preventing the information loss problem while maintaining adaptability across different device form factors and display resolutions
Solution Approach 2:
The patent introduces an intermediary assessment system between the image source and electronic devices. This intermediary evaluates image legibility using multiple criteria (text components, connected components, overall image assessment) and provides feedback to prevent distribution of illegible images, thereby resolving the contradiction between downsizing for adaptability and maintaining text legibility
2Measurement precision
If manual assessment of image legibility is performed, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The system enables self-service automated assessment of image legibility through multiple evaluation modules. The text component assessment, connected component assessment, and overall image assessment all operate automatically without requiring human intervention, thereby maintaining high measurement precision while dramatically improving productivity by processing images at machine speed
Solution Approach 2:
The patent replaces manual mechanical assessment with automated computational systems. Multiple assessment modules (text component analysis, connected component analysis, overall image assessment) use algorithmic processing to evaluate legibility, substituting human manual review with automated systems that achieve both high precision and high productivity
3Productivity
If automated assessment is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The automated assessment system is segmented into distinct functional modules: text component assessment, connected component assessment, and overall image assessment. Each module handles specific aspects of legibility evaluation independently, which manages system complexity by breaking down the overall task while maintaining high productivity through parallel or sequential processing of multiple images
Data Source
AI summary
In some implementations, legibility of an image may be automatically determined based, at least in part, on text contained in the image. For example, image analysis techniques may be used to identify text components in an image. One or more features of each text component may be determined for use in assessing the legibility of the text component. For example, a classifier trained on the one or more features may provide a confidence level indicative of the legibility of each text component. The confidence level for each of the text components may be compared to a legibility threshold for determining whether the text component is legible or illegible. Based, at least in part, on the determination as to how much of the text in the image is legible or illegible, an overall legibility of the image may be assessed.