Character Recognition Apparatus for Misrecognized Character Removal
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Solution Overview
Problem
Camera-based character recognition systems face high misrecognition rates due to ambient light and environmental influences, leading to inconvenient manual removal of misrecognized characters, especially when background is included in the image.
Innovation Solution
A method and apparatus that convert input images into binary images, detect character regions, perform morphology operations to enlarge and connect character regions, and reclassify invalid regions with fewer characters as non-character regions, thereby removing misrecognized characters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If camera-based character recognition is used to recognize characters in various environments, then the versatility of character recognition is improved, but the misrecognition rate increases due to ambient light and environmental influences
Solution Approach 1:
The patent segments the photographed image into document regions and background regions using edge detection and region merging algorithms. By dividing the image into distinct regions, the system can focus character recognition only on document regions, thereby maintaining versatility in various environments while improving recognition accuracy by excluding background interference.
Solution Approach 2:
The patent introduces an intermediary processing stage between image capture and character recognition that automatically identifies and separates document regions from backgrounds. This intermediary region discrimination mechanism acts as a mediator that filters out environmental interference before character recognition occurs, resolving the contradiction between versatility and accuracy.
2Area of stationary object
If the character recognizing apparatus attempts to recognize characters in the entire photographed image including background, then the coverage of recognition is improved, but the number of misrecognized characters increases
Solution Approach 1:
The system segments the photographed image into multiple regions including document regions and background regions. By performing recognition only on identified document regions rather than the entire image area, the system maintains effective coverage of relevant content while improving reliability by excluding background areas that would cause misrecognition.
Solution Approach 2:
The patent applies different processing qualities to different regions: document regions undergo character recognition processing while background regions are excluded. This local differentiation in processing quality ensures that recognition coverage focuses on relevant areas with high reliability, rather than uniformly processing the entire image area.
3Measurement precision
If manual selection of document region is required for accurate recognition, then the recognition accuracy is improved, but the ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically identifying and selecting document regions without requiring user intervention. The edge detection and region merging algorithms autonomously discriminate document regions from backgrounds, maintaining high recognition accuracy while eliminating the need for manual region selection, thereby improving ease of operation.
Solution Approach 2:
The patent performs preliminary automatic document region identification before the user needs to interact with the system. By pre-processing the image to identify and isolate document regions, the system prepares the data in advance, ensuring both high recognition accuracy and user convenience without requiring manual selection steps.
4Quantity of substance
If the photographed image includes both document and background, then the completeness of image capture is improved, but the difficulty of detecting character regions increases
Solution Approach 1:
The patent segments the complete photographed image into document regions and background regions using edge detection and region merging. This segmentation approach preserves the completeness of the captured image content while systematically reducing the detection difficulty by organizing the image into distinct, analyzable regions with clear boundaries.
Solution Approach 2:
The system performs preliminary processing to identify and organize character regions within the complete image before recognition occurs. By pre-segmenting the image into document and background regions, the system maintains completeness of captured content while simplifying subsequent character region detection through structured region organization.
Data Source
AI summary
Disclosed is a method and an apparatus for recognizing a character and efficiently removing a misrecognized character. The method includes detecting character regions including at least one character in an input image, converting the input image into a binary image, discriminating the characters from a non-character, re-classifying the character region including a number of characters equal to or less than a threshold into a non-character region, and outputting only the characters present in the character region.