Image Data Structure Recognition for Efficient UI Import
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Solution Overview
Problem
Current technologies face challenges in efficiently importing and presenting data from images captured by cameras, particularly in recognizing and processing tabular data, and providing immediate feedback and graphical representations within a user interface.
Innovation Solution
The system employs an information detection engine (IDE) using optical character recognition (OCR) enhanced by machine learning to recognize text and detect structure in images, allowing users to capture, manipulate, and visualize data in real-time within a user interface, enabling interactive data import and presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data import methods are used, then data can be entered into the system, but the process is time-consuming and inefficient
Solution Approach 1:
The patent replaces manual mechanical data entry operations with automated optical character recognition (OCR) technology. The system captures images of documents containing tabular data, automatically recognizes and extracts the data using OCR engines, and imports it into the business intelligence system, eliminating the need for manual typing or copying of data.
Solution Approach 2:
The system enables self-service data import by allowing users to simply capture images of data sources with a mobile device camera. The automated processing pipeline including OCR recognition, data structure detection, and validation operates without requiring manual intervention, making the data import process autonomous and user-friendly.
2Loss of information
If traditional data import processes are used, then data can be transferred, but immediate feedback and visualization are not provided
Solution Approach 1:
The patent implements real-time feedback mechanisms throughout the data import process. The system provides immediate visual feedback during image capture by overlaying detected data structures on the captured image, shows recognition progress and results as data is being processed, and displays validation status, enabling users to monitor and verify the import process in real-time.
Solution Approach 2:
The system performs preliminary data processing and visualization actions during the capture phase itself. By detecting and visualizing data structures in real-time as the image is being captured, the system prepares and validates data before final import completion, providing early feedback on what will be imported and allowing users to make adjustments if needed.
3Measurement precision
If comprehensive data detection and processing is performed, then accurate data import is achieved, but system complexity increases
Solution Approach 1:
The patent divides the complex data import process into distinct modular segments: image capture module, OCR recognition module, data structure detection module, validation module, and visualization module. Each module handles a specific aspect of the process independently, making the overall complex system manageable and maintainable while achieving high accuracy through specialized processing at each stage.
Data Source
AI summary
Implementations generally relate to importing data and presenting the data in a user interface (UI). In some implementations, a method includes capturing an image of an object using a camera, where the object includes text. The method further includes recognizing the text and recognizing data in a table. The method further includes generating a data structure that includes the text or the data in the table. The method further includes generating a graphical image that represents at least a portion of the text or the data in the table. The method further includes displaying the graphical image in a UI in a display screen of a client device.