OCR Text Recognition Accuracy via Contextual Meaning Disambiguation
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Solution Overview
Problem
Conventional Optical Character Recognition (OCR) processes often produce inaccurate text from images due to issues like lack of focus, contrast, and incomplete textual strings, leading to insufficient information for further processing or user action.
Innovation Solution
The system enhances OCR by identifying significant words or phrases in images, using topical information and database entries to determine meanings, and retrieving additional relevant data, such as author or publication information, to provide a more immersive experience for users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional OCR processes are used to identify text in images, then text recognition can be performed, but the accuracy and completeness of the recognized text is insufficient due to image quality issues
Solution Approach 1:
The system uses feedback mechanisms where the processed image and recognized text are fed back into the system to generate corrections and refinements. The processor identifies errors in the initially recognized text by comparing against the image data and generates corrected text output, continuously improving accuracy through iterative feedback loops.
Solution Approach 2:
An intermediary correction mechanism is introduced between the OCR processing and final output. The system includes a correction module that acts as an intermediary, analyzing the relationship between image data and recognized text to identify and correct errors before the final text output is generated, thereby improving both accuracy and completeness.
2Ease of operation
If additional information is retrieved and displayed for selected words or phrases, then user interaction and information accessibility are improved, but system complexity and processing time increase
Solution Approach 1:
The system extracts and isolates specific words or phrases from the recognized text for which additional information needs to be retrieved. By taking out only the relevant portions rather than processing the entire text, the system reduces unnecessary processing complexity while maintaining the ability to provide enhanced user interaction and information accessibility where needed.
Solution Approach 2:
The information retrieval and display process is segmented into discrete units corresponding to individual words or phrases. The system processes and displays additional information for each selected unit separately, which divides the complex task into manageable segments, reducing overall system complexity while preserving ease of operation for users.
3Loss of information
If the system processes and displays additional information for recognized text, then the usefulness of OCR output is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by processing and retrieving additional information only for selected words or phrases rather than the entire text. This selective approach provides sufficient information usefulness for user needs while significantly reducing processing time and computational resources compared to processing all text content.
Solution Approach 2:
The system performs preliminary identification and selection of words or phrases that are most likely to benefit from additional information retrieval. By pre-selecting and prioritizing relevant terms before executing the full information retrieval process, the system minimizes unnecessary processing time while ensuring that the most useful information is obtained.
Data Source
AI summary
Disclosed are techniques for providing additional information for text in an image. In some implementations, a computing device receives an image including text. Optical character recognition (OCR) is performed on the image to produce recognized text. A word or a phrase is selected from the recognized text for providing additional information. One or more potential meanings of the selected word or phrase are determined. One of the potential meanings is selected based on other text in the image. A source of additional information corresponding to the selected meaning is selected for providing the additional information to a user's device.