Mobile Remittance Image Capture with Server-Side Geometric Correction
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Solution Overview
Problem
Current systems for processing remittance coupons using mobile devices face challenges in capturing and processing images efficiently due to issues like poor image quality, perspective distortion, and the need for image enhancement, which can lead to errors in data extraction and processing.
Innovation Solution
The system involves a mobile device capturing images of remittance coupons, which are then transmitted for image optimization and enhancement, including geometric correction, quality assessment, and processing, using a server-based system that includes modules for image correction, quality assurance testing, and remittance processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If images are captured using mobile devices, then ease of operation is improved, but image quality deteriorates due to perspective distortion and poor focus
Solution Approach 1:
The system performs preliminary actions by capturing multiple images at different focuses and perspectives before final processing. The focus assessment module evaluates multiple focus states and selects or synthesizes the best focus, while perspective distortion correction is applied in advance to prepare images for accurate data extraction.
Solution Approach 2:
An intermediary processing system is introduced between the mobile device camera and the final data extraction process. This intermediary includes image optimization modules that correct perspective distortion, adjust focus, and enhance image quality, thereby bridging the gap between easy mobile capture and high processing accuracy.
2Manufacturing precision
If image optimization and enhancement are applied, then image quality is improved, but processing time increases
Solution Approach 1:
The system applies local quality enhancement by selectively optimizing only the portions of the image that require attention. The focus assessment module identifies specific regions with poor focus or distortion and applies correction only to those areas, rather than processing the entire image uniformly, thereby reducing overall processing time.
Solution Approach 2:
The system applies partial action by implementing image optimization based on assessed quality thresholds. If an image meets minimum quality standards, full optimization is skipped; if quality is insufficient, targeted optimization is applied only to the extent necessary to meet processing requirements, avoiding excessive processing time on already adequate images.
3Reliability
If multiple image quality tests are executed, then reliability of data extraction is improved, but device complexity increases
Solution Approach 1:
The quality assurance process is segmented into distinct, modular tests: focus assessment, perspective distortion detection, and other quality metrics. Each test is independent and can be executed separately, allowing the system to manage complexity through modular design while maintaining comprehensive reliability checking.
Solution Approach 2:
The system performs preliminary quality assessment tests before the main data extraction process. By conducting focus and distortion checks in advance, the system can filter out poorly quality images early, reducing the complexity of subsequent processing and ensuring that only suitable images undergo full analysis.
Data Source
AI summary
The present invention relates to automated document processing and more particularly, to methods and systems for document image capture and processing using mobile devices. In accordance with various embodiments, methods and systems for document image capture on a mobile communication device are provided such that the image is optimized and enhanced for data extraction from the document as depicted. These methods and systems may comprise capturing an image of a document using a mobile communication device; transmitting the image to a server; and processing the image to create a bi-tonal image of the document for data extraction. Additionally, these methods and systems may comprise capturing a first image of a document using the mobile communication device; automatically detecting the document within the image; geometrically correcting the image; binarizing the image; correcting the orientation of the image; correcting the size of the image; and outputting the resulting image of the document.