Optical Code Recognition Apparatus for 1D Color Bit Codes
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Solution Overview
Problem
Conventional two-dimensional barcode cutout methods fail to accurately recognize and extract 1D color bit codes due to distortion, blurring, and variations in dimension and shape, especially when multiple codes are present in an image, requiring complex image recognition and precise positioning.
Innovation Solution
A method for reading 1D color bit codes that extracts cells satisfying the marking pattern conditions from entire image data without auxiliary signs, using a simple imaging process and recognizing patterns across the entire image, allowing for efficient recognition and decoding even when multiple codes exist in a single image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional two-dimensional barcode cutout methods are used to extract 1D color bit codes, then the recognition accuracy deteriorates due to distortion and shape variations, but the device complexity remains high requiring complex image recognition and positioning
Solution Approach 1:
The patent segments the image processing task by first detecting candidate regions based on color distribution characteristics, then independently analyzing each candidate region for code patterns. This divides the complex global recognition problem into simpler local analysis tasks, improving accuracy while reducing overall processing complexity
Solution Approach 2:
The patent changes the approach from geometric parameter-based recognition (shape, position, orientation) to color parameter-based recognition (color distribution, color sequences). This parameter transformation makes the recognition robust against distortion and shape variations, achieving high accuracy without complex positioning
2Measurement precision
If conventional cutout methods with auxiliary signs are used, then the positioning precision improves, but the ease of manufacture deteriorates due to requirement for precise positioning and auxiliary patterns
Solution Approach 1:
The patent extracts and removes the requirement for auxiliary cutout patterns and precise positioning from the system. By using color-based candidate region detection, it eliminates the need for manually designed auxiliary signs, simplifying device implementation while maintaining extraction precision through automated color analysis
Solution Approach 2:
The code itself provides the necessary information for recognition through its color patterns. The 1D color bit code's inherent color sequences and distributions serve as self-identifying features, eliminating the need for external auxiliary signs and making the system easier to manufacture and implement
3Adaptability or versatility
If multiple 1D color bit codes are present in a single image, then the adaptability improves, but the difficulty of detecting and measuring increases due to need for complex cutout patterns
Solution Approach 1:
The patent segments the image into multiple candidate regions based on color distribution characteristics, then independently processes each candidate region. This segmentation approach naturally handles multiple codes in a single image, improving adaptability while reducing detection difficulty by treating each code as a separate, simpler recognition task
Solution Approach 2:
The patent uses color parameter analysis (color histograms, color sequences) that can be independently applied to multiple regions simultaneously. This parameter-based approach scales well to multiple codes, enhancing adaptability without proportionally increasing detection difficulty, as the same color analysis methods apply to each code regardless of quantity
Data Source
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AI summary
According to the present invention, there is provided an optical recognition code recognizing apparatus for recognizing an optical recognition code, comprising dividing means for dividing image data obtained by imaging an optical recognition code into color areas based on parameters indicative of colors, and determining means for determining whether each of the divided color areas is a cell as a component of the optical recognition code or not.