Image Text Replacement for Readability Enhancement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Individuals with poor vision or those unfamiliar with a language face challenges in comprehending text due to its small size, poor quality, or foreign languages, especially in images and videos, where text is often indistinguishable from the background and requires advanced recognition techniques.
Innovation Solution
The conversion of graphically represented text into process-capable text, such as Unicode, for computer processing, and subsequent translation into a more readable format, which can be integrated back into the image to enhance visibility and comprehension, using modules for text detection, translation, and output enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If text is presented in small size or poor quality in images, then image information density is improved, but text readability deteriorates
Solution Approach 1:
The system extracts text from the original image using optical character recognition (OCR), separates it from the image background, and processes it independently. This extraction allows the text to be enhanced without altering the original image composition, resolving the contradiction between maintaining image information density and improving text readability.
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between the original image and the final output. The system uses OCR as an intermediary to convert image text to machine-readable format, then applies enhancement techniques, and finally integrates the enhanced text back into the image or presents it separately, thus improving readability without compromising the original image.
2Loss of information
If text is presented in foreign languages with many characters, then information expression capacity is improved, but text comprehension deteriorates
Solution Approach 1:
The system introduces translation software as an intermediary that bridges the gap between foreign language text and the viewer's native language. The OCR system first extracts the foreign text, then translation software converts it to the viewer's language, and finally the translated text is presented in an enhanced format, maintaining information expression capacity while improving comprehension.
Solution Approach 2:
The patent replaces the mechanical process of human language learning and character recognition with automated software systems. Instead of requiring viewers to understand foreign characters, the system uses OCR and translation software to automatically convert and translate text, substituting manual cognitive effort with automated processing.
3Shape
If text is scripted or poorly written in images, then image artistic quality is improved, but text detection difficulty increases
Solution Approach 1:
The system employs feedback mechanisms where the OCR software analyzes the detected text quality and adjusts its recognition parameters accordingly. When text is poorly written or artistically styled, the system can request alternative interpretations, adjust contrast and clarity enhancements, or use multiple recognition passes to improve detection accuracy without compromising the original artistic quality.
Data Source
AI summary
Image text enhancement techniques are described. In an implementation, graphically represented text included in an original image is converted into process capable text. The process capable text may be used to generate a text image which may replace the original text to enhance the image. In further implementations the process capable text may be translated from a first language to a second language for inclusion in the enhanced image.