OCR Document Indexing With Parallel Confirmation and Rule Updates
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Solution Overview
Problem
Existing image processing systems face challenges in efficiently scanning multiple documents, dividing them into files, and recommending file names and transmission destinations while automatically learning index extraction rules, leading to increased user workload and waiting times due to repetitive operations and difficulty in applying updated rules to subsequent documents.
Innovation Solution
An image processing apparatus that performs OCR on multiple documents in parallel, generates file name recommendations, and allows simultaneous user confirmation and correction, updating index extraction rules based on user input, thereby reducing user workload and waiting times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If image processing for recommendation is executed first at a back end of confirmation operation, then waiting time is reduced, but newly registered index extraction rules cannot be applied to other documents in the same scanning process
Solution Approach 1:
The system performs preliminary image processing and generates recommendation results for all scanned documents before presenting them to the user for confirmation. This preliminary action completes the time-consuming OCR and analysis work in advance, reducing the waiting time users experience. The recommendation results are prepared and ready, allowing the system to quickly display options without delaying the user workflow.
Solution Approach 2:
The system dynamically updates index extraction rules based on user corrections during the scanning process. When users confirm or correct recommendation results, the system learns from this feedback and updates its rules in real-time. This dynamic adaptation allows newly registered rules to be immediately applied to subsequent documents within the same scanning process, making the system increasingly accurate as it progresses.
2Reliability
If a series of processing from recommendation to reception of confirmation result is repeated for each file, then accurate file management is achieved, but user workload and waiting time increase
Solution Approach 1:
The system merges the processing of multiple documents into a single batch operation. Instead of presenting confirmation UIs sequentially for each document, the system collects recommendation results for all scanned documents and presents them together in one confirmation interface. Users can review and confirm multiple file names, transmission destinations, and folder assignments simultaneously, dramatically reducing the number of repetitive interactions required while maintaining accurate file management through individual confirmation options.
3Measurement precision
If manual operation for file name assignment and meta-information assignment is performed, then accurate document classification is achieved, but user workload increases with the number of documents
Solution Approach 1:
The system performs automatic document classification and recommendation generation without requiring manual user input for each document. The OCR unit automatically extracts text and metadata from scanned documents, the image processing unit generates recommendation results including file names and transmission destinations based on learned index extraction rules, and the system presents these recommendations for user confirmation. This self-service approach maintains high classification accuracy through intelligent algorithms while dramatically improving digitization efficiency by eliminating repetitive manual operations.
Data Source
AI summary
An image processing apparatus according to an aspect of the present disclosure includes an optical character recognition (OCR) unit configured to sequentially execute processing related to OCR on image data on a plurality of documents, a generation unit configured to select one of the plurality of documents subjected to the processing related to OCR, and to generate a recommendation content about an index to be assigned to the one selected document based on an index extraction rule, and a confirmation unit configured to present the generated recommendation content to a user and to assign an index to the one document based on an instruction from the user. The processing to be executed by the OCR unit and processing to be executed by the confirmation unit are executed in parallel.