Mobile Document Image Capture Preview Analysis
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Solution Overview
Problem
Mobile devices struggle to capture high-quality images of documents for electronic processing due to varying image quality, which is time-consuming and cumbersome for users to evaluate and improve.
Innovation Solution
A system that captures multiple preview images of a document, analyzes parameters related to image quality, and selects the best image based on criteria such as focus, exposure, and text extraction ability, allowing for automatic image capture and real-time feedback to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple preview images are captured and analyzed to ensure high image quality, then image quality and OCR accuracy are improved, but the time required for image capture and evaluation increases
Solution Approach 1:
The system captures multiple preview images at lower quality settings before the final image capture. These preview images are used to evaluate focus, exposure, and composition parameters in advance, allowing the system to determine when to capture the final high-quality image, thereby reducing overall capture time while ensuring quality.
Solution Approach 2:
The system creates multiple copies (preview images) of the document at different quality levels. These copies are analyzed to select the optimal capture parameters for the final image, eliminating the need for repeated high-quality captures and reducing time loss.
2Manufacturing precision
If manual evaluation of image quality is performed by the user, then image quality can be controlled, but the process becomes time-consuming and cumbersome
Solution Approach 1:
The system performs automatic evaluation of image quality parameters (focus, exposure, composition) using computer vision algorithms. The system self-determines whether the captured image meets quality thresholds and automatically selects or requests retakes, eliminating manual user evaluation and significantly improving ease of operation.
Solution Approach 2:
The system provides real-time feedback to users about image quality through visual indicators and automatic determination of capture readiness. This feedback mechanism guides users without requiring manual evaluation, maintaining quality control while simplifying the user experience.
3Measurement precision
If image quality parameters are evaluated in real-time, then the accuracy of extracted text is improved, but the processing complexity increases
Solution Approach 1:
The image quality evaluation process is segmented into multiple independent parameter assessments (focus detection, exposure analysis, composition evaluation). Each parameter is evaluated separately using dedicated algorithms, making the overall complex process more manageable and efficiently implementable on mobile devices.
Solution Approach 2:
Manual or complex mechanical image evaluation processes are replaced with automated computer vision algorithms and machine learning models that can efficiently assess image quality parameters. This substitution reduces processing complexity while maintaining or improving measurement precision for text extraction.
Data Source
AI summary
Real-time evaluation of high quality preview images of a document prior to capturing a final image of the document on a mobile device is disclosed. In one aspect, an image capture device is activated on the mobile device. A plurality of preview images of the document is then captured, each of which has a lower image quality than a final image to be captured by the image capture device. Next, for each of the plurality of preview images, the system measures a parameter associated with the image capturing, and related to the ability to accurately extract text and other content from a captured preview image of the document. Next, the system selects a preview image among a subset of the captured preview images that passes the image quality measurement. When a predetermined condition is met, the system chooses the selected preview image as a final captured image of the document.