Multi-Check Video Capture With Geometric Front-and-Back Matching
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Solution Overview
Problem
Existing technologies face challenges in effectively capturing clear, unobstructed images of both sides of multiple documents, particularly checks, during remote deposit capture, due to issues like piggybacking, blurry images, and manual matching of front and back sides, which is tedious, prone to errors, and time-consuming.
Innovation Solution
The system employs image correction, rejection alerts, and automated front-to-back side matching using geometrical features to automatically pair images of the front and back sides of checks, utilizing scanners and cameras for multiple document capture, with video capture and image processing to ensure clarity and alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual matching of front and back sides of checks is performed, then image capture can be completed, but the process becomes tedious, prone to errors, and time-consuming
Solution Approach 1:
The system performs self-service by automatically matching front and back images of checks using image processing algorithms. The system extracts features from images, compares them, and automatically pairs corresponding front and back sides without human intervention, thereby eliminating manual matching while maintaining accuracy
Solution Approach 2:
The patent replaces the mechanical/manual process of visually inspecting and matching check sides with an automated image processing system. Computer vision algorithms analyze image characteristics such as check number, date, and visual patterns to automatically associate front and back images, substituting human manual work with automated computational processes
2Productivity
If multiple checks are captured using traditional scanning methods, then documents can be processed, but issues like piggybacking and blurry images occur
Solution Approach 1:
The system implements feedback mechanisms where captured images are immediately evaluated for quality metrics such as focus, lighting, and completeness. The system provides real-time feedback to identify piggybacking situations or blurry images and can request recaptures or automatically adjust processing parameters to ensure high-quality image pairs are produced
Solution Approach 2:
The patent employs parameter changes by adjusting capture settings such as focus distance, lighting intensity, and image resolution dynamically during the capture process. The system modifies these parameters based on detected conditions to optimize image quality while maintaining high capture speed across multiple checks
3Manufacturing precision
If automated image correction is applied, then image quality improves, but system complexity increases
Solution Approach 1:
The image correction system is segmented into distinct functional modules: focus detection module, lighting adjustment module, alignment module, and quality validation module. Each module handles a specific aspect of image correction independently, making the overall complex system more manageable and easier to implement through modular architecture
Data Source
AI summary
Systems and techniques may be used to perform multi-capture for remote deposit via video. For example, a technique may include capturing a first video of a first side and a second video of the second side of each of a plurality of checks, and extracting a first set of respective individual images of the first side and the second side of each check of the plurality of checks. The technique may include comparing geometrical features of the first side of each of the plurality of checks to geometrical features of the second side of each of the plurality of checks, and based on the comparison, selecting an image from the first set of respective individual images that corresponds to an image from the second set of respective individual images to form a pair of images.