Associating Objects with N-Dimensional Symbols via Random Pattern Matching
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Solution Overview
Problem
Objects that cannot be attached with an n-dimensional symbol, such as QR codes, due to lack of space or other constraints, cannot be associated with such symbols using existing methods.
Innovation Solution
A system and method that captures and associates an n-dimensional symbol with a random pattern drawn on the object using cameras and a server, allowing the object to be linked with the symbol even if direct attachment is not possible, by capturing and matching images of the pattern with pre-registered symbols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an n-dimensional symbol is directly attached to an object, then the object can be associated with the symbol, but objects without space for attachment cannot be associated with the symbol
Solution Approach 1:
The patent uses a random pattern as a visual copy or representation of the object's surface, which can be captured and associated with the n-dimensional symbol without requiring physical attachment. The random pattern serves as a surrogate that maintains the association relationship while avoiding the need for actual symbol attachment to the object surface.
Solution Approach 2:
The random pattern acts as an intermediary element between the object and the n-dimensional symbol. Instead of directly attaching the symbol to the object, the system captures the random pattern on the object's surface and uses this pattern as a mediator to establish the association with the n-dimensional symbol through image processing and matching.
2Adaptability or versatility
If a random pattern is captured and matched to associate objects with n-dimensional symbols, then objects without attachment space can be associated with symbols, but the system complexity increases
Solution Approach 1:
The system creates a digital copy of the random pattern on the object's surface through image capture. This copy is then processed and matched against stored patterns to establish associations, eliminating the need for complex physical attachment mechanisms while introducing computational processing steps.
Solution Approach 2:
The patent replaces mechanical attachment systems with an optical and computational system. Instead of physically attaching symbols to objects, the system uses cameras to capture random patterns and computational algorithms to match and associate objects with n-dimensional symbols, substituting mechanical operations with optical and information processing operations.
Data Source
AI summary
A system includes: an acquiring unit that acquires an image of an n-dimensional symbol; a first image capturing unit that captures an image of a random pattern on a surface of an object; a storing unit that stores the image of the n-dimensional symbol and a first image that is the image of the random pattern captured by the first image capturing unit in a manner that the images are associated with each other; a second image capturing unit that captures an image of a random pattern on a surface of an object; a matching unit that performs matching of the image captured by the second image capturing unit against the first image stored by the storing unit; and a displaying unit that displays the image of the n-dimensional symbol associated with the first image stored by the storing unit based on the result of the matching.