Claim Document Character Recognition via Region Segmentation
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Solution Overview
Problem
Current OCR technologies for recognizing characters in insurance claim documents suffer from low recognition precision, requiring significant human and material resources for verification, leading to inefficiencies and document recording mistakes.
Innovation Solution
A method involving region segmentation based on the frame line layout of claim document images, followed by analysis using a CNN or LSTM model to differentiate between easily recognizable and difficult regions, employing appropriate recognition engines or models for each, thereby improving character recognition precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional OCR technology is used for character recognition in claim documents, then automation is improved, but recognition precision deteriorates
Solution Approach 1:
The patent divides the claim document into multiple regions based on frame line layout (e.g., claim number region, claim content region, signature region). Different recognition strategies are applied to different regions: simple OCR for clear regions, enhanced preprocessing for difficult regions. This segmentation allows the system to maintain high automation while improving overall recognition precision by treating different document areas with appropriate methods.
2Productivity
If traditional OCR technology is used for character recognition, then processing speed is improved, but recognition precision deteriorates, leading to more verification needs
Solution Approach 1:
The patent applies different quality levels of processing to different document regions. For regions with clear, standard formatting (like claim numbers), simple fast OCR is used. For regions with handwritten text or complex layouts (like claim content), more sophisticated preprocessing and multiple recognition passes are applied. This local quality approach maintains high processing speed for simple regions while ensuring high precision for difficult regions, reducing overall verification needs.
3Device complexity
If uniform recognition processing is applied to all document regions, then device complexity is reduced, but recognition precision deteriorates
Solution Approach 1:
The patent implements a dynamic recognition system that automatically adjusts processing strategies based on document characteristics. The system first performs region segmentation, then analyzes each region's characteristics (handwritten vs. printed, clarity, layout complexity) to dynamically select appropriate recognition methods. This dynamic approach achieves high precision without requiring manually configured complex systems for each document type, as the system adapts automatically.
Data Source
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AI summary
The disclosure discloses a method, device and server of recognizing characters of a claim document, and a storage medium. The method includes: after the server receives a claim document image to be subjected to character recognition, performing region segmentation according to the frame line layout of a claim document frame format, thus obtaining one or multiple segmented regions; and calling a predetermined analysis model to analyze all the obtained segmented regions , and respectively performing character recognition on all the analyzed segmented regions by using a predetermined recognition rule to recognize characters in all the segmented regions. In the disclosure, in consideration of the influence of the claim document frame format on the recognition precision, the region segmentation is firstly performed according to the frame line layout of the claim document frame format before the character recognition, and then the character recognition is performed on all the segmented regions, so that the influence and the interference of frame lines in the document on the character recognition during uniform recognition of the characters in the whole claim document image are avoided, and the recognition precision for the characters in the claim document can be effectively improved.