QR Code Transaction Data Encoding for Receipt Management
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Solution Overview
Problem
Current financial management systems, such as tax preparation and receipt management applications, face challenges in accurately importing data due to inconsistencies in image capture quality, lighting, paper condition, and varying document formats, leading to inaccuracies in OCR-based data importation.
Innovation Solution
The implementation of a two-dimensional machine-readable representation, specifically a Quick Response (QR) code, encodes transaction data, allowing for accurate decoding and population of electronic receipt summaries, eliminating reliance on OCR and accommodating different document formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If Optical Character Recognition (OCR) is used to import data from images, then data importation is enabled, but data accuracy deteriorates due to inconsistencies in image capture quality, lighting, paper condition, and document formats
Solution Approach 1:
The patent creates a machine-readable representation (MRR) that is a standardized copy of the transaction data, independent of the original image quality. The MRR serves as a perfect digital copy that can be decoded accurately regardless of OCR failures, resolving the contradiction between automated data importation and data accuracy.
Solution Approach 2:
The machine-readable representation acts as an intermediary between the physical receipt and the electronic database. Instead of directly converting receipt images to data (which fails due to image inconsistencies), the system uses the MRR as an intermediate carrier that guarantees accurate data transmission, solving the accuracy problem while maintaining automation.
2Measurement precision
If manual data entry is used to ensure accuracy, then data accuracy is maintained, but time consumption increases
Solution Approach 1:
The system enables self-service data extraction where the machine-readable representation on the receipt automatically provides the data needed. Users simply scan the MRR and the system automatically extracts and validates the data, eliminating the need for manual typing while ensuring accuracy through the structured format of the MRR.
Solution Approach 2:
The merchant system performs preliminary action by encoding transaction data into the machine-readable representation at the point of sale. This pre-processing ensures the data is ready for accurate extraction later, eliminating the need for manual entry while maintaining accuracy, thus reducing user time investment.
3Adaptability or versatility
If OCR algorithms are used to handle varying document formats, then compatibility is improved, but reliability deteriorates due to format inconsistencies and recognition errors
Solution Approach 1:
The patent changes the fundamental parameter of data representation from variable-format text (which OCR processes) to a standardized machine-readable code structure. This parameter change allows the system to handle different document formats universally while ensuring reliable decoding, as the MRR format remains consistent regardless of the underlying receipt layout variations.
Data Source
AI summary
Transaction or receipt data, e.g., data of a receipt document, is encoded as a two-dimensional machine readable representation, such as a QR CODE. Certain receipt data is encoded as segments of a QR CODE. An image of the QR CODE is acquired using a camera of a mobile communication device or computer or other image capture device. The QR CODE image is decoded to determine the receipt data, and fields of an electronic receipt summary can be populated with decoded data.