Chart Data Recognition via Contextual Analysis
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Solution Overview
Problem
Current technologies are inefficient and error-prone when processing images of printed documents with complex text arrangements, often requiring manual interpretation and data entry, leading to a less than desirable user experience.
Innovation Solution
Techniques are developed to interpret graphical data in images, determining values and chart types, and generating editable data structures such as spreadsheets, allowing users to modify and process the data through touch-enabled controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If OCR technologies are used to convert printed documents into text files, then text recognition is improved, but complex formats and contextual markings still require manual interpretation and data entry
Solution Approach 1:
The patent introduces an intermediary system between OCR text recognition and final data output. This intermediary includes contextual analysis modules that interpret markings, symbols, and complex formats, automatically converting them into structured data without requiring manual intervention. The system acts as a mediator that bridges the gap between simple text recognition and complex data extraction.
Solution Approach 2:
The patent replaces the mechanical manual data entry process with an automated computational system. Instead of human operators manually interpreting and entering data from complex formats, the system uses algorithmic processes to automatically parse, interpret, and convert various document formats into structured data, eliminating the need for manual mechanical data entry operations.
2Reliability
If manual interpretation and data entry are performed to ensure correct information entry, then data accuracy is improved, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent implements a self-service system where the document processing system automatically performs interpretation and data extraction tasks that would traditionally require human operators. The system uses built-in contextual analysis, pattern recognition, and validation mechanisms to independently ensure data accuracy without manual intervention, making the system self-sufficient while maintaining high reliability.
Solution Approach 2:
The patent applies preliminary validation and verification steps within the automated processing workflow. Before final data output, the system performs preliminary checks on data accuracy, contextual consistency, and format compliance, ensuring that errors are detected and corrected automatically during the processing sequence rather than requiring post-processing manual verification.
3Productivity
If current OCR technologies are used for complex document formats, then basic text extraction is achieved, but error-prone manual processes are still required
Solution Approach 1:
The patent incorporates feedback mechanisms where the system continuously monitors and validates extracted data against contextual information and expected patterns. When discrepancies or potential errors are detected, the system automatically adjusts its interpretation or requests clarification, creating a closed-loop process that reduces error rates while maintaining high processing speeds through iterative refinement rather than slow manual verification.
Data Source
AI summary
An image including a chart displaying graphical elements may be received or captured by a computing device. The graphical elements, for example, may be bars of a bar chart, or components of a pie chart. Techniques described herein may determine values for the graphical elements. Techniques described herein may also analyze the arrangement of the graphical elements and other contextual information to determine a chart type. The generated values may be arranged into an editable chart and/or an editable data structure based on the chart type. Touch-enabled gestures may be applied to the data structure to allow a user to modify, save or otherwise process the data structure.