Server-Based Character Recognition Accuracy Correction
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Solution Overview
Problem
The accuracy of optical character recognition (OCR) systems needs improvement, as they often suffer from misrecognition errors that current technologies fail to effectively address.
Innovation Solution
A character recognition system comprising a server apparatus and a terminal apparatus connected via a network, where the server analyzes the recognition results from the terminal, identifies misrecognition, and transmits specific data to improve the recognition process, including specifying character types and adjusting parameters for more accurate OCR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard character recognition is performed by the terminal apparatus, then processing speed is maintained, but recognition accuracy deteriorates due to misrecognition errors
Solution Approach 1:
A server apparatus is introduced as an intermediary between the terminal apparatus and the character recognition process. The server receives image data from the terminal, performs advanced character recognition with multiple engines, and returns correction information. This mediator enables improved accuracy without requiring the terminal apparatus itself to become more complex.
Solution Approach 2:
The system performs preliminary character recognition at the terminal apparatus to obtain initial results quickly. When misrecognition is detected, the system then performs a second, more thorough recognition process at the server. This preliminary action allows the system to maintain fast processing for clear images while only applying complex processing when necessary.
2Measurement precision
If advanced character recognition processing is performed, then recognition accuracy improves, but processing time increases
Solution Approach 1:
The system applies advanced processing selectively rather than universally. It performs basic recognition first, then applies additional processing only to characters or regions where misrecognition is suspected. This partial action approach maintains high accuracy for problematic areas while avoiding unnecessary processing time for already-clear characters.
Solution Approach 2:
The terminal apparatus performs preliminary character recognition to identify candidates quickly. Only when misrecognition is detected does the system engage in the more time-consuming advanced processing at the server. This two-stage approach minimizes overall processing time while ensuring accuracy when needed.
3Measurement precision
If multiple character recognition engines are used, then recognition accuracy improves, but device complexity increases
Solution Approach 1:
Multiple character recognition engines are merged and centralized in the server apparatus rather than being distributed across multiple terminal apparatuses. This consolidation allows the system to leverage the strengths of different engines (e.g., one optimized for English, another for Japanese) to improve overall accuracy while maintaining a manageable system architecture.
4Measurement precision
If character type specification is performed, then recognition accuracy improves, but processing complexity increases
Solution Approach 1:
Character type specification is applied locally to specific regions or characters where misrecognition is detected, rather than applying it universally to the entire image. The server identifies problematic areas and applies targeted character type constraints only to those regions, improving accuracy without the overhead of processing the entire image with full complexity.
Data Source
AI summary
A method disclosed herein uses a processor of a server to function as a processing unit to enhance accuracy of character recognition in a terminal connected to the server, using a communication apparatus of the server. The processing unit may be configured to acquire first data indicating a result of character recognition with respect to image data taken by the terminal. The processing unit can determine a character type of a character included in the image data when it is determined that misrecognition is included in the result of character recognition based on the first data. The processing unit controls the communication apparatus to transmit second data according to the character type to terminal and instructs the terminal to perform character recognition using the second data with respect to the image data in order to improve the accuracy of character recognition.