Scan Avoidance Detection Using Timeout Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In retail environments, scan avoidance events can occur due to accidental or intentional actions, leading to loss of revenue and unnecessary alerts, which can embarrass customers and delay transactions, and existing solutions often rely on expensive and complex neural networks or image processing systems that are not feasible for all stores.
Innovation Solution
A computer-implemented method and system that detects potential scan avoidance by identifying non-transaction affecting indicia during a timeout period and generating an alarm signal when transaction affecting indicia is not identified or decodable, using an imaging assembly and barcode decoder within a symbology scanner, without requiring complex neural networks or image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex neural networks or image processing systems are used to detect scan avoidance events, then detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the detection task into distinct phases: capturing multiple images during a timeout period, decoding indicia from each image, and analyzing decode results sequentially. This breakdown allows the system to achieve accurate scan avoidance detection through simple, discrete operations rather than requiring a complex neural network to process the entire task at once.
Solution Approach 2:
The system performs preliminary actions by capturing multiple images during a timeout period before making a final scan avoidance determination. The barcode decoder attempts to decode indicia from each captured image in advance, and the scan avoidance event detector analyzes these pre-decoded results to confirm whether scan avoidance occurred, eliminating the need for complex real-time image analysis.
2Reliability
If scan avoidance detection systems are implemented, then revenue loss from theft is reduced, but false alerts increase causing customer embarrassment and transaction delays
Solution Approach 1:
The system uses feedback from multiple decode attempts during a timeout period to confirm scan avoidance events. The barcode decoder provides feedback about whether indicia were successfully decoded from each captured image, and the scan avoidance event detector uses this feedback to make a confident determination only when all decode attempts fail, reducing false alerts while maintaining theft prevention effectiveness.
Solution Approach 2:
The patent applies partial action by attempting to decode indicia from only some of the captured images rather than requiring analysis of all images. The scan avoidance event detector determines scan avoidance when the barcode decoder fails to identify or decode transaction affecting indicia from the captured images during the timeout period, which is sufficient to confirm theft without requiring excessive processing that could increase false positives.
Data Source
AI summary
Methods of detecting scan avoidance events during decode sessions are disclosed herein. An example method includes during a timeout period at one or more processors of the symbology scanner, identifying and decoding a transaction affecting indicia on an object in one or more images to obtain a transaction affecting payload; during the timeout period at the one or more processors, identifying one or more visual features in the one or more images; and in response to identifying a non-transaction affecting indicia associated with the one or more visual features, and failing to identify or decode the transaction affecting indicia, determining a potential scan avoidance attempt and generating a scan avoidance alarm signal.