Image Type Verification for Mixed Document Bundles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face a burden when documents of a type different from the designated type are mixed with a bundle read by the image reading apparatus, requiring them to manually remove the mixed document and re-designate the type for re-scanning, which is inefficient.
Innovation Solution
An information processing apparatus that acquires images, determines if they match a designated type, and if not, presents alternative types to the user for re-designation, reducing the need for manual intervention by automatically suggesting and processing images of unclear types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the image reading apparatus reads documents without type verification, then reading speed is improved, but document type accuracy deteriorates causing mixed types to be read
Solution Approach 1:
The system performs preliminary type verification by comparing read documents against registered type definitions before final processing. This preliminary check identifies mismatched documents without requiring full processing, enabling quick detection and removal of incorrect types while maintaining overall reading efficiency.
Solution Approach 2:
The system implements feedback mechanisms where type verification results are fed back into the reading process. When documents of incorrect types are detected, the system provides feedback to adjust the reading operation, such as stopping the feed or alerting the user, preventing further mixing of document types.
2Measurement precision
If the system performs manual removal and re-designation of mixed documents, then document type accuracy is improved, but operation burden increases
Solution Approach 1:
The system performs self-service by automatically detecting, identifying, and managing documents of incorrect types. The type verification unit and type determination unit work autonomously to classify documents and trigger appropriate actions without requiring manual user intervention for each individual document.
Solution Approach 2:
The system prepares and registers multiple document type definitions in advance, creating a library of expected document formats. This preliminary preparation enables the system to quickly match and verify document types during the reading process without requiring users to manually specify or learn complex classification rules.
3Ease of operation
If the system automatically detects and processes mixed document types, then operation burden is reduced, but system complexity increases
Solution Approach 1:
The system segments the document processing function into distinct modular units: a type verification unit that checks document types, a type determination unit that identifies correct types, and a reading control unit that manages the reading process. This segmentation allows each unit to perform its specific function independently, simplifying the overall system architecture while providing comprehensive automatic verification.
Solution Approach 2:
The type verification unit serves multiple functions: it verifies document types against registered definitions, identifies mismatched documents, determines correct document types, and controls the reading process accordingly. This multi-functionality reduces the need for separate specialized components, managing system complexity while providing comprehensive automatic document type management.
Data Source
AI summary
An information processing apparatus includes a processor configured to acquire an image, receive designation of a type of the image, present another type specified from the image in a case where the type does not satisfy a criterion corresponding to the image, and receive re-designation of a type of the image.