Receipt Image Acquisition Using Optical Character Recognition and Stitching
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Solution Overview
Problem
Existing methods for acquiring and processing receipt information are cumbersome and inefficient, as they require manual collection and processing of physical receipts, which is often burdensome and lacks effective automation.
Innovation Solution
A system comprising an image acquisition device and image analysis software that uses OCR algorithms and contextual information to automatically scan, analyze, and extract textual data from receipts, allowing for real-time or near-real-time processing and creation of composite images for improved quality, and utilizing feedback mechanisms to guide users for optimal image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual collection and processing of physical receipts is used, then user control and simplicity are maintained, but productivity and time efficiency deteriorate
Solution Approach 1:
The system enables self-service by automatically capturing receipt images through the camera, performing OCR text extraction, and processing data without requiring user intervention in manual data entry. The receipt is scanned, processed, and stored automatically, eliminating the need for manual collection and processing while maintaining simplicity for the end user.
Solution Approach 2:
The patent replaces manual mechanical processes (physical handling, sorting, and data entry of receipts) with automated electronic systems including image capture devices, OCR software, and database storage. This substitution dramatically increases productivity while the automated nature handles the complexity, presenting only a simple scan action to the user.
2Measurement precision
If single frame image capture is used, then device simplicity is maintained, but image quality and measurement precision deteriorate
Solution Approach 1:
The system merges multiple image frames into a single composite image through image stitching technology. Multiple captures are combined to create a high-quality, complete receipt image that exceeds the quality of any single frame, enabling accurate OCR processing while the system manages the complexity of multi-frame processing automatically.
Solution Approach 2:
The system performs preliminary actions by capturing multiple frames and processing them through stitching and quality enhancement before the final OCR extraction. This preliminary image preparation ensures high measurement precision for text recognition while the complexity is handled in advance, presenting a simple result to the user.
3Productivity
If automated OCR and image analysis are implemented, then productivity and information extraction efficiency are improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent introduces an intermediary layer of image processing and preprocessing between the camera capture and final OCR extraction. This intermediary stage includes steps like image stitching, enhancement, and preparation that bridge the gap between raw images and OCR-ready formats, improving extraction efficiency while managing software complexity through modular processing steps.
Solution Approach 2:
The system creates digital copies of physical receipts through image capture and processing. Instead of handling physical documents, the system works with digital replicas that can be automatically processed, stored, and analyzed. This copying approach enables high productivity through automated OCR while the software complexity is contained within the digital processing pipeline rather than physical handling procedures.
4Area of stationary object
If multiple frames are combined for composite imaging, then image quality and field of view are improved, but processing time and complexity increase
Solution Approach 1:
The system employs periodic action by capturing multiple frames in rapid succession and processing them through a standardized stitching algorithm. The periodic capture and processing approach allows for efficient batch handling of images, expanding the field of view to capture complete receipts while managing processing time through systematic, repetitive operations that can be optimized and parallelized.
Data Source
AI summary
Systems and methods are presented for acquisition of receipt information using portable scanning devices such as a cellphone camera running suitable software. A smartphone having associated software is used to capture image from a receipt, by holding the smartphone camera over the receipt such that the latter is within the field of view of the cellphone camera. The software may be adapted to automatically identify receipts when such appear in the camera's field of view, and to automatically capture images. Compositing multiple images, image stitching, and OCR are all employed as necessary by the system to extract textual information from receipts.