Mobile Document Image Quality Assurance System
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Solution Overview
Problem
The quality of images captured by mobile devices is often inadequate for electronic processing of documents due to various factors such as camera characteristics and environmental conditions, leading to geometrical defects and poor image quality.
Innovation Solution
A mobile document image quality assurance system that assesses the quality of images captured by mobile devices using preprocessing and test execution modules, selecting appropriate tests based on document type, mobile application, and device characteristics, and rejecting images that fail quality tests while providing feedback to users for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If images are captured using mobile devices, then image capture becomes convenient and accessible, but image quality deteriorates due to camera characteristics and environmental conditions
Solution Approach 1:
The system performs preliminary quality assessment actions immediately after image capture by executing a plurality of quality tests on the captured image. These tests evaluate geometric properties, image clarity, and other quality metrics before the image is accepted for processing, allowing preventive rejection of poor quality images before they cause problems downstream.
Solution Approach 2:
The system provides feedback to users about the quality of captured images by displaying test results and quality assessments. This feedback mechanism informs users whether their captured image meets the required standards and guides them in retaking the image if necessary, creating a closed-loop system that improves image quality through user guidance.
2Reliability
If multiple quality tests are performed on captured images, then image quality assurance is improved, but processing time increases
Solution Approach 1:
The quality assessment process is segmented into multiple independent tests, each evaluating specific aspects of image quality such as geometric properties, clarity, and other metrics. This segmentation allows the system to execute tests in parallel or prioritize critical tests, improving overall efficiency while maintaining comprehensive quality assurance.
Solution Approach 2:
The system executes a plurality of quality tests, including some that may not be strictly necessary, to ensure thorough quality assessment. By performing excessive testing, the system maximizes quality assurance and minimizes false accepts, even though it increases processing time. The trade-off is justified by the high stakes of incorrect processing.
3Measurement precision
If images are rejected that fail quality tests, then processing accuracy is improved, but user experience deteriorates due to false rejects
Solution Approach 1:
The system adjusts quality test parameters and thresholds dynamically based on the specific requirements of different processing applications. By tailoring test parameters to match the actual processing needs, the system reduces false rejects while maintaining high processing accuracy, ensuring that only truly insufficient images are rejected.
Data Source
AI summary
Techniques for assuring the quality of mobile document image captured using a mobile device are provided. These techniques include performing one or more tests to assess the quality of images of documents captured using the mobile device. The tests can be selected based on the type of document that was imaged, the type of mobile application for which the image quality of the mobile image is being assessed, and/or other parameters such as the type of mobile device and/or the characteristics of the camera of the mobile device that was used to capture the image. The image quality assurance techniques can also be implemented on can be implemented on a mobile device and/or on a remote server where the mobile device routes the mobile image to the remote server processing and the test results are be passed from the remote server to the mobile device.