Paper Aging Detection Using Dynamic Pixel Grayscale Thresholds
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Solution Overview
Problem
Existing methods for identifying stained banknotes are inefficient due to the aging of the paper-like medium affecting stain determination, leading to errors when using new paper-like medium pixel values as references.
Innovation Solution
A method and device that acquire pixel grayscale values from a paper-like medium, determine the aging level by comparing average grayscale values with aging thresholds, and adjust stain determination based on the aging level using region-specific stain thresholds to accurately assess stain levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pixel values of new paper-like medium are used as reference for stain determination, then the stain detection is simple and fast, but the determination accuracy deteriorates when the paper-like medium is old
Solution Approach 1:
The patent applies preliminary action by pre-establishing multiple reference pixel value sets corresponding to different aging levels before actual stain detection. When a paper-like medium is detected, its aging level is first determined, and the corresponding pre-prepared reference set is selected, avoiding the need to manually adjust references during detection and maintaining both speed and accuracy.
Solution Approach 2:
The patent changes the reference parameter (pixel grayscale values) according to the aging level of the paper-like medium. Different aging levels have different reference pixel value ranges, allowing the stain determination to adapt to the specific condition of the medium being tested, thus resolving the contradiction between using fixed simple references and needing accurate variable references.
2Measurement precision
If manual selection of stained banknotes is performed, then the determination accuracy can be ensured, but the labor cost and time consumption increase significantly
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated image processing system. The system uses pixel grayscale analysis and aging-level-based reference comparison to automatically determine stain levels, eliminating the need for manual selection while maintaining or improving accuracy through consistent, objective criteria.
Solution Approach 2:
The system performs self-service by automatically determining the aging level of the paper-like medium and selecting the appropriate reference standard without external intervention. The automated comparison between detected pixel values and age-appropriate references enables the system to independently make accurate stain determinations without requiring manual oversight for each item.
3Device complexity
If a single reference standard is used for all paper-like mediums, then the system complexity is reduced, but the adaptability to different aging levels deteriorates
Solution Approach 1:
The patent segments the reference system into multiple distinct reference pixel value sets, each corresponding to a specific aging level. This segmentation allows the system to handle different aging conditions with appropriate specialized references while maintaining a structured, manageable organization that doesn't excessively increase complexity.
Solution Approach 2:
The patent creates a universal reference system that serves multiple aging levels through a standardized multi-level framework. The same basic system structure and processing methodology are used across all aging levels, providing universality in approach while accommodating diversity in reference values, thus achieving both simplicity and adaptability.
Data Source
AI summary
A paper identifying method and a related device, used for accurately identifying soilage conditions of paper according to the recency degree of the paper. The method in an embodiment of the present invention comprises: obtaining a pixel gray value group of an image of input paper, the pixel gray value group being a combination of gray values of sampled pixels of a specified region of the input paper; obtaining an average value of gray values of all pixels in the pixel gray value group, and using same as a first average gray value; comparing the first average gray value with a recency threshold to determine the recency level of the input paper; obtaining the soilage depth of each of N regions of the input paper, the N being an integer greater than or equal to 1; and determining the soilage level of the input paper according to the soilage depth of the N regions, the region area and a soilage threshold, the soilage threshold corresponding to the recency level.