Virtual Boundary Symbol Identification on Variable Objects
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Solution Overview
Problem
Conventional imaging systems struggle to accurately identify symbols on moving objects with varying sizes and orientations, especially at tight gapping conditions, often requiring complex and costly depth-from-scale analysis and dimensioning systems, which are time-consuming to set up and can be inaccurate due to reflection interference.
Innovation Solution
The system employs processor devices to determine a characteristic object dimension, allowing for the identification of virtual leading and trailing boundary features in images, enabling the determination of symbol placement on objects without the need for precise actual dimension measurement, thus simplifying the system design and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth-from-scale analysis and dimensioning systems are used to identify symbols on moving objects, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a characteristic object dimension (a simplified copy or representation of the actual object dimension) to establish virtual boundary features instead of requiring precise measurement of each individual object. This copying approach maintains sufficient accuracy for symbol identification while dramatically reducing system complexity and cost.
Solution Approach 2:
The patent changes the measurement parameter from actual object dimensions to characteristic object dimensions. By using a standardized characteristic dimension that represents the set of objects, the system achieves adequate measurement precision without the complexity of depth-from-scale analysis, resolving the contradiction between accuracy and system simplicity.
2Manufacturing precision
If depth-from-scale analysis is used to account for varying object sizes, then manufacturing precision is improved, but setup time increases
Solution Approach 1:
The patent performs preliminary action by establishing virtual boundary features based on characteristic object dimensions before actual symbol identification occurs. This pre-establishment of boundaries using standardized dimensions eliminates the need for time-consuming depth-from-scale analysis during operation, reducing setup time while maintaining precision.
Solution Approach 2:
The patent changes from using actual measured dimensions to characteristic dimensions that are predetermined. This parameter change allows the system to maintain manufacturing precision for symbol placement identification while eliminating the time-consuming measurement and analysis setup process.
3Productivity
If conventional imaging systems are used for tight gapping conditions, then productivity is maintained, but measurement precision deteriorates
Solution Approach 1:
The patent introduces virtual boundary features as an intermediary between the imaging system and symbol identification process. These virtual boundaries, established using characteristic dimensions, serve as reference markers that enable accurate symbol identification even in tight gapping conditions where objects are closely spaced, maintaining both productivity and precision.
4Device complexity
If characteristic object dimension is used instead of actual dimension, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent uses a characteristic object dimension as a simplified copy that represents the set of objects rather than measuring each individual object. This copying approach reduces device complexity significantly while maintaining sufficient measurement precision for the intended application of symbol identification, as the characteristic dimension captures the essential dimensional characteristics needed for virtual boundary establishment.
Data Source
AI summary
A system or method can analyze symbols on a set of objects having different sizes. The system can identify a characteristic object dimension corresponding to the set of objects. An image of a first object can be received, and, a first virtual object boundary feature (e.g., edge) in the image can be identified for the first object based on the characteristic object dimension. A first symbol can be identified in the image, and whether the first symbol is positioned on the first object can be determined, based on the first virtual object boundary feature.


