Image Processing System for Document Character Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for optimizing character recognition in documents with complex backgrounds or high-speed scanning often result in insufficient recognition accuracy due to inadequate binarization and noise issues, and are inefficient in determining optimal image processing settings.
Innovation Solution
An information processing system that analyzes captured images to select recommended setting values for image processing parameters, such as background pattern removal and noise reduction, by repeatedly trying different settings to achieve the highest character recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing settings are manually adjusted to improve character recognition accuracy, then recognition accuracy improves, but the time required to determine optimal settings increases
Solution Approach 1:
The system performs preliminary analysis of the captured image to extract document type information, background pattern information, and text density information before the actual character recognition process. This preliminary action enables the automatic selection of appropriate image processing settings without requiring manual trial and error, thus improving recognition accuracy while reducing the time needed to determine optimal settings
Solution Approach 2:
The system evaluates multiple candidate image processing settings by performing test character recognition and comparing results against reference data. The feedback from these evaluations is used to automatically select the optimal settings combination, eliminating manual adjustment time while ensuring high recognition accuracy through systematic optimization
2Measurement precision
If multiple image processing settings are tested to find optimal parameters, then character recognition accuracy improves, but processing complexity increases
Solution Approach 1:
The image processing optimization is divided into separate modules: document type classification, background pattern detection, text density analysis, and setting selection. Each module handles a specific aspect of the optimization process independently, reducing overall processing complexity while maintaining the ability to evaluate multiple settings combinations for high recognition accuracy
Solution Approach 2:
The system changes processing parameters systematically based on document characteristics. Instead of exhaustively testing all possible settings, the system adjusts parameters like binarization threshold, noise reduction strength, and background removal intensity according to the detected document type and text density, simplifying the search process while achieving optimal recognition accuracy
3Productivity
If standard binarization processing is used for high-speed scanning, then processing speed improves, but recognition accuracy deteriorates due to noise
Solution Approach 1:
The system applies different image processing techniques to different regions of the document based on local characteristics. For example, areas with heavy noise receive stronger noise reduction processing, while clean areas use standard binarization. This localized approach maintains high processing speed for most areas while improving accuracy in problematic regions
Solution Approach 2:
The system dynamically adjusts the strength of noise reduction and background pattern removal based on the detected noise level and document type. For high-speed scanning of clean documents, minimal processing is applied to maintain speed. For documents with complex backgrounds or high noise, the system automatically increases processing intensity to preserve recognition accuracy
Data Source
AI summary
An information processing system includes circuitry. The circuitry acquires a captured image by capturing a document. The circuitry performs an analysis process using the captured image. The circuitry selects, for each of at least one setting item of a plurality of setting items relating to image processing to be performed on the captured image, at least one setting value from among configurable setting values as a candidate for a recommended setting. The circuitry performs image processing repeatedly on the captured image while changing setting values of the plurality of setting items with a setting value of the at least one setting item restricted to the at least one setting value selected as the candidate for the recommended setting. The circuitry determines recommended settings for the plurality of setting items relating to image processing to obtain an image suitable for character recognition.