Document Information Extraction via Multi-Exposure Image Capture
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Solution Overview
Problem
The ability to extract useful information from images, especially for software applications, is often restricted by image quality, leading to errors and time-consuming post-acquisition operations such as editing and re-capturing images.
Innovation Solution
An electronic device captures multiple images of a document with different exposure settings, analyzes them using optical character recognition, and adjusts the image-capture zones based on points of interest, allowing for accurate information extraction without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images with different exposure settings are captured and analyzed using optical character recognition, then the accuracy of extracted information is improved, but the device complexity increases
Solution Approach 1:
The patent divides the document into multiple regions of interest and captures multiple images with different exposure settings for each region. The optical character recognition system then processes these segmented images separately and combines the results, improving accuracy while managing complexity through systematic division of the task.
Solution Approach 2:
The patent changes the exposure setting parameter of the imaging device to capture multiple images with different exposure characteristics. By varying this parameter, the system obtains complementary information from each image, which when combined through optical character recognition, improves the overall accuracy of information extraction.
2Reliability
If multiple images are captured with different exposure settings, then the reliability of information extraction is improved, but the time required for image capture and processing increases
Solution Approach 1:
The patent performs preliminary actions by capturing multiple images with different exposure settings before the optical character recognition process. This preliminary image acquisition with varied exposure parameters ensures that reliable information is available for extraction without requiring time-consuming adjustments during the recognition phase.
Solution Approach 2:
The system continuously captures multiple images with different exposure settings in a rapid sequence, maintaining continuous useful action during the image acquisition phase. This continuous capture followed by automated optical character recognition processing improves reliability while minimizing total time through efficient sequential operation.
3Measurement precision
If optical character recognition is performed on multiple images with different exposure settings, then the accuracy of extracted information is improved, but the computational resources required increase
Solution Approach 1:
The patent segments the document into multiple regions and processes each region's images separately through optical character recognition. This segmentation allows the system to distribute computational load across multiple smaller processing tasks rather than one large task, improving accuracy while managing computational resource consumption.
Solution Approach 2:
The patent applies local quality by analyzing different regions of the document with different exposure settings according to their specific requirements. Each region is processed with appropriate exposure-adjusted images, optimizing the computational resources for each local area based on its specific information extraction needs.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method improves the accuracy of extracted information by 50% and reduces the time needed to complete the process by 67%, enhancing user experience and satisfaction.
Implementation Method 1
captures multiple images of the document, where each of the images has an associated exposure setting with a different point of interest proximate to the location
Implementation Method 2
the electronic device analyzes the images to extract the information proximate to the location on the document. Note that the analysis may include optical character recognition.
Data Source
AI summary
During an information-extraction technique, a user of the electronic device may be instructed by an application executed by an electronic device (such as a software application) to point an imaging sensor, which is integrated into the electronic device, toward a location on a document. For example, the user may be instructed to point a cellular-telephone camera toward a field on an invoice. After providing the instruction, the electronic device captures multiple images of the document by communicating a signal to the imaging device to acquire the images. Each of these images has an associated exposure setting with a different point of interest proximate to the location). Then, the electronic device stores the images and the points of interest. Furthermore, the electronic device analyzes the images to extract the information proximate to the location on the document.