Dynamic OCR Selection for Document Processing Efficiency
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Solution Overview
Problem
Current optical character recognition (OCR) systems in multifunction peripherals (MFPs) face inefficiencies in converting image data to character code data, with varying recognition rates and costs associated with different conversion processing sections, leading to suboptimal document processing.
Innovation Solution
An information processing system with multiple conversion processing sections (first and second conversion processing sections) that can convert image data to character code data, allowing selection based on recognition rates and costs, enabling flexible and efficient document processing by selecting the appropriate conversion processing section for each document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single conversion processing section is used for OCR processing, then the device complexity is reduced, but the recognition rate and processing efficiency deteriorate
Solution Approach 1:
The OCR processing system is divided into multiple independent conversion processing sections (first conversion processing section and second conversion processing section), each capable of performing OCR independently. This segmentation allows the system to achieve high recognition rates by selecting appropriate processing sections while maintaining manageable complexity through modular design.
2Measurement precision
If multiple conversion processing sections are used for OCR processing, then the recognition rate is improved, but the device complexity increases
Solution Approach 1:
The system dynamically selects which conversion processing section to use based on the input image characteristics and processing requirements. The selection section determines the appropriate processing section in real-time, allowing the system to achieve high recognition rates without permanently maintaining complex multi-section infrastructure for all operations.
Solution Approach 2:
Multiple conversion processing sections are designed with universal capabilities to handle various types of documents and images. Each section can independently perform OCR processing, making them multi-functional units that reduce overall system complexity while maintaining high recognition performance through selective deployment.
3Stability of the object's composition
If the first conversion processing section is used for all documents, then the processing consistency is maintained, but the cost-effectiveness and adaptability deteriorate
Solution Approach 1:
Different conversion processing sections are assigned to different types of documents or processing scenarios based on their specific strengths and cost-effectiveness. The selection section determines the appropriate section for each document, allowing locally optimized processing while maintaining overall system consistency through standardized selection criteria.
Data Source
AI summary
An information processing system includes an image reading device and an information processing device. The image reading device reads a document to generate target image data. The information processing device processes the target image data. The information processing device includes a first conversion processing section, a second conversion processing section, and a selection section. The first conversion processing section is capable of converting image data to character code data. The second conversion processing section is capable of converting image data to character code data. The selection section selects conversion of the target image data to character code data by the first conversion processing section or the second conversion processing section.