Physical Asset Recognition via Image-Based Context Parsing
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Solution Overview
Problem
Existing systems face challenges in automatically identifying the intended recipient of a physical asset from ambiguous or incomplete information on labels, often requiring manual human intervention, which is inefficient and prone to errors.
Innovation Solution
A method using image processing techniques to determine an identifier associated with a physical asset by identifying regions of graphically encoded and textual data, parsing spatial templates, and selecting the appropriate identifier based on context and historical data, allowing for automated determination and notification of the intended recipient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual human intervention is used to interpret and transcribe information on physical asset labels, then accuracy can be maintained, but processing efficiency and speed deteriorate
Solution Approach 1:
The patent replaces manual human interpretation and transcription of label information with an automated image processing system. The system captures images of physical assets, uses optical character recognition to extract text from labels, and automatically matches extracted information with database records to identify recipients, eliminating the need for manual mechanical transcription while maintaining accuracy.
Solution Approach 2:
The system enables self-service by allowing the physical asset label itself to provide all necessary information through machine-readable codes and printed text. The automated system reads this information directly from the label without requiring human intervention to interpret or transcribe it, making the identification process self-contained and automated.
2Productivity
If automated image processing is used to extract information from physical asset labels, then processing efficiency improves, but accuracy deteriorates due to ambiguous or incomplete information
Solution Approach 1:
The patent merges multiple information sources and processing techniques into a unified system. It combines image capture, optical character recognition, graphically encoded data interpretation, and database matching to create a robust automated identification system that overcomes the limitations of any single method when dealing with ambiguous or incomplete label information.
Solution Approach 2:
The system incorporates feedback mechanisms where the automated image processing extracts information from the physical asset label, matches it with database records, and can iteratively refine the identification process. The system uses the extracted information to query the database, receives feedback from the database results, and adjusts its interpretation to improve accuracy in identifying the correct recipient.
3Measurement precision
If comprehensive information is collected from multiple regions of the physical asset label, then identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the label information processing into distinct regions and data types. The system identifies and processes different regions of the label separately (such as text regions, bar code regions, QR code regions), extracting information from each segment and then integrating the results. This segmentation approach manages complexity by handling each region with appropriate specialized processing while achieving comprehensive identification accuracy.
Data Source
AI summary
One or more processors receives one or more first database records indicating a plurality of candidate identifiers are received by one or more processors. The one or more processors obtains one or more electronic images of the physical asset. At least one electronic image includes a graphical representation of data printed on the physical asset. The one or more processors identifies a plurality of regions of the data based on the one or more electronic images. The one or more processors determines a context of the physical asset based on the plurality of regions, selects the identifier from the plurality of candidate identifiers based on the plurality of regions, and generates a second database record including an indication of the context of the physical asset, and an indication of the identifier.