Composite Document Imaging for Readable Remote Check Deposit
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Solution Overview
Problem
Existing systems for remote check depositing face challenges in capturing and processing digital images due to issues like focus, resolution, glare, and other optical image capture difficulties, which burden the payee with time and effort in depositing checks.
Innovation Solution
A system using a mobile device with a camera and processor captures multiple images of a document, analyzes them to identify acceptable portions, combines these portions to generate a composite image, and transmits it to a depository, or recaptures designated portions that fail quality criteria to create a composite image for transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single digital image is captured for remote check deposit, then the deposit process is simplified, but the image quality may be insufficient due to focus, glare, or resolution issues
Solution Approach 1:
The patent divides the document into multiple regions of interest (front side, back side, corners, edges) and captures separate images of each region. This segmentation allows the system to obtain multiple high-quality images of specific areas rather than relying on a single comprehensive image, thereby resolving the contradiction between operational simplicity and image quality.
Solution Approach 2:
The system captures more images than traditionally required by taking multiple photographs of different portions of the document from various angles and distances. This excessive action ensures that at least some images meet the required quality standards, overcoming the limitation of single-image capture while maintaining an automated process.
2Manufacturing precision
If multiple images are captured to ensure quality, then image readability improves, but the time and effort required for deposit increases
Solution Approach 1:
The system automatically captures, selects, and processes multiple images without requiring user intervention. The mobile device's processor autonomously performs image capture, quality assessment, and selection of acceptable images, eliminating the need for manual image taking and review by the user. This self-service approach maintains high image readability while minimizing the time and effort burden on the user.
Solution Approach 2:
The system implements a feedback mechanism where captured images are automatically evaluated against quality criteria, and the system determines whether additional images are needed. This automated feedback loop ensures that only the necessary number of images are captured to meet quality standards, optimizing the balance between image readability and deposit time.
3Productivity
If the system requires perfect image capture in one attempt, then processing efficiency is maintained, but user frustration increases due to optical challenges
Solution Approach 1:
The system performs preliminary actions by automatically capturing multiple images of different document portions before any quality assessment occurs. By pre-capturing a set of diverse images, the system ensures that at least some will meet quality standards regardless of optical challenges, thereby maintaining processing efficiency while reducing user frustration.
Solution Approach 2:
The system varies capture parameters such as camera position, distance, angle, and lighting conditions across multiple images. By changing these parameters, the system increases the probability of obtaining at least one high-quality image that meets processing requirements, thereby maintaining efficiency while improving user experience.
4Loss of information
If the system captures comprehensive document images, then all information is available for processing, but focus and resolution issues arise in certain areas
Solution Approach 1:
The patent divides the document into multiple segments (front side, back side, corners, edges) and captures separate images of each segment. This segmentation allows the camera to focus on specific areas with appropriate lighting and distance, ensuring high local image quality while collectively capturing all necessary document information across multiple images.
Solution Approach 2:
The system applies different capture conditions to different document regions, optimizing image quality for each specific area. By capturing close-up images of corners and edges with appropriate focus and lighting, the system ensures that each region meets the required quality standards while maintaining complete information coverage across all captured images.
Data Source
AI summary
Systems and methods are provided herein that can include capturing a plurality of images of a document, analyzing the plurality of images to identify a plurality of acceptable portions within the plurality of images, combining the plurality of acceptable portions to generate a composite image of the document, and transmitting the composite image to a depository. Additionally or alternatively, the systems and methods can include capturing an image of a document, identifying a designated portion of the captured image of the document that fails to satisfy a predetermined image quality criteria, recapturing an image of only the designated portion of the document, generating a composite image from the captured image of the document and the recaptured image of only a portion of the document, and transmitting the composite image of the document to a depository via a communication pathway.