Spreadsheet OCR Image Data Association
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Solution Overview
Problem
The existing methods for interacting with data, such as electronic spreadsheets, are time-consuming and error-prone when dealing with non-electronic data sources like printed receipts or handwritten lists, requiring manual typing which is inefficient and prone to errors.
Innovation Solution
A spreadsheet application integrates data from captured images using optical character recognition (OCR) technology, automatically translating and associating the image data with a spreadsheet, including formatting and formulas, and allows for comparison and updating of existing data, as well as creating augmented displays like charts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual typing is used to enter data from printed receipts or handwritten lists into spreadsheets, then data can be entered into the spreadsheet, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces the mechanical manual typing process with optical character recognition (OCR) technology that uses cameras to capture images of printed receipts or handwritten lists and automatically converts them into digital data. This substitution eliminates the need for manual keyboard input, thereby increasing both productivity and reducing errors associated with manual typing.
Solution Approach 2:
The patent creates optical copies (images) of the source documents (receipts, lists) and uses image recognition algorithms to extract data from these copies. This copying approach allows the system to capture the exact visual representation of the data, including formatting and structure, and automatically transfer it to the spreadsheet without manual intervention.
2Ease of operation
If manual data entry is used, then data can be transferred from paper to electronic format, but the process is tedious and time-consuming
Solution Approach 1:
The system performs self-service by automatically capturing images, recognizing text and data patterns, extracting relevant information, and populating spreadsheet cells without requiring user intervention for each data entry step. The automated workflow handles the entire data transfer process from paper to electronic format, significantly reducing both time and operational complexity.
Solution Approach 2:
The patent performs preliminary actions by pre-processing the captured images through OCR, pattern recognition, and data validation before actual data entry into the spreadsheet. This preliminary processing prepares the data in the correct format and structure, enabling rapid and accurate population of spreadsheet cells without manual formatting or validation steps.
3Loss of information
If data is manually typed into spreadsheets, then data can be entered, but formatting and structural information from the source document is lost
Solution Approach 1:
The patent applies parameter changes by detecting and preserving various data attributes including text formatting (bold, italic, underline), color information, font styles, cell positioning, and hierarchical structure from the source document. These parameters are extracted during image processing and applied to the corresponding spreadsheet cells, maintaining the visual and structural characteristics of the original data.
Solution Approach 2:
The system uses a nested approach where multiple layers of data extraction and processing occur: first extracting basic text content, then identifying structural elements (tables, lists, headings), followed by detecting formatting attributes, and finally organizing all this information into the spreadsheet hierarchy. This nested processing ensures comprehensive preservation of source document characteristics.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution streamlines the data entry process by automatically converting and integrating image data into spreadsheets, reducing errors and increasing efficiency, while allowing for accurate representation and visualization of the data through enhanced displays.
Implementation Method 1
A spreadsheet application associates data obtained from a captured image with a spreadsheet. For example, one or more images of data may be captured and translated into electronic data that is automatically associated with one or more spreadsheets.
Data Source
AI summary
A spreadsheet application associates data obtained from a captured image with a spreadsheet. For example, one or more images of physical data may be captured and translated into electronic data that is automatically associated with one or more spreadsheets. The formatting and underlying formulas of the data included within the captured image may be represented within a spreadsheet (e.g. highlighted data remains highlighted within the electronic spreadsheet). The data may also be compared with existing electronic data. For example, differences between the data in the captured image with the data in an existing spreadsheet may be used to update the existing spreadsheet. A display of a captured image may be also be augmented using data that is obtained from the captured image. For example, a chart may be created and displayed using data that is obtained from the captured image.