Scan Data Processing Device for Document Identification and Error Detection
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Solution Overview
Problem
Existing document processing systems face challenges in accurately collecting and sorting electronic data from documents with identification codes, leading to errors such as mix-ups or loss of pages, which are difficult to detect without manual visual confirmation.
Innovation Solution
An information processing device and method that acquires identification information from documents using scan data, generates extraction data by collecting electronic data associated with the identification information, and performs different processing based on set constraint conditions to improve usability and workability during combined sorting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic collection of electronic data is performed without constraint checking, then processing speed is improved, but error detection capability deteriorates
Solution Approach 1:
The system automatically checks whether the collected electronic data satisfies predetermined constraint conditions (such as page number constraints) and provides feedback by generating notification information when constraints are violated. This feedback mechanism enables automatic error detection without manual intervention, resolving the contradiction between processing speed and error detection capability.
Solution Approach 2:
The system performs preliminary checking of constraint conditions during the data collection process itself, rather than after completion. By validating data against predetermined constraints in advance, the system prevents erroneous data from being processed further, maintaining both speed and reliability.
2Reliability
If manual visual confirmation is performed to detect reading errors, then error detection capability is improved, but processing time increases
Solution Approach 1:
The system performs self-verification by automatically checking whether the collected electronic data satisfies predetermined constraint conditions. This self-service capability eliminates the need for manual visual confirmation, allowing the system to detect its own errors automatically and reduce processing time while maintaining reliability.
Solution Approach 2:
The system generates notification information that automatically informs users of constraint violations, providing feedback without requiring manual inspection. This feedback mechanism enables rapid error detection and reduces the time users would otherwise spend visually confirming data accuracy.
3Productivity
If extraction data is collected without constraint conditions, then productivity is improved, but data accuracy deteriorates
Solution Approach 1:
The system changes the parameters of data collection by introducing and enforcing predetermined constraint conditions (such as minimum and maximum page numbers) during the extraction process. This parameter modification ensures that only data satisfying specific criteria is collected, improving accuracy without significantly impacting collection speed.
Solution Approach 2:
The system performs preliminary filtering of data based on constraint conditions during the collection process. By pre-establishing criteria such as page number ranges, the system ensures accurate data selection in advance, maintaining both high productivity and data accuracy.
Data Source
AI summary
An information processing device includes: a storage unit configured to store scan data read from a plurality of documents; and a processing unit configured to acquire, based on the scan data, identification information corresponding to an identification code present in the document, and generate, based on the scan data, extraction data obtained by collecting electronic data of the documents associated with the identification information among the plurality of documents. The processing unit analyzes the extraction data and performs processing corresponding to an analysis result.