Checkout Mis-Scan Detection via Hand and Item Tracking
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Solution Overview
Problem
Current retail checkout systems fail to accurately detect mis-scans of items during the purchasing process, leading to potential errors and inefficiencies, as they lack effective mechanisms to identify items not scanned correctly or intentionally avoided.
Innovation Solution
A system comprising a scanner, camera, and control circuit that captures identifiers and images of items at a checkout station, detects the user's hand and scanner, and initiates mis-scan detection by tracking items from a staging location to a bagging area, using image processing and machine learning to determine if items have been scanned, thereby identifying and addressing mis-scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional checkout systems are used without advanced detection mechanisms, then the system complexity remains low, but the reliability of detecting mis-scans deteriorates
Solution Approach 1:
The system divides the detection task into multiple components: a camera captures images of items at the checkout station, a control circuit processes these images to detect items, and a scanner captures identifiers. This segmentation allows each component to specialize in a specific function, improving overall detection reliability while managing system complexity through modular architecture.
Solution Approach 2:
The camera acts as an intermediary between the physical items and the detection system. By capturing images of items and their identifiers, the camera provides visual data that the control circuit can process to determine whether items were scanned, enabling reliable mis-scan detection without requiring direct physical interaction with each item.
2Measurement precision
If image processing and machine learning are implemented for mis-scan detection, then the measurement precision of item scanning improves, but the use of energy and computational resources increases
Solution Approach 1:
The system applies image processing and machine learning selectively rather than continuously. The control circuit processes images to detect items and determine whether they were scanned, applying computational resources only when needed to resolve detection uncertainty, thus balancing measurement precision with energy consumption.
Solution Approach 2:
The system uses the visual information already present in the checkout environment (items and their identifiers) to perform self-detection. By analyzing images of items and comparing them with scanner data, the system autonomously determines whether mis-scans occurred without requiring additional external energy-intensive measurement devices.
3Reliability
If continuous monitoring of items is implemented from staging location to bagging area, then the reliability of item tracking improves, but the device complexity and processing time increase
Solution Approach 1:
The system captures images of items at the checkout station in advance of the actual scanning process. By having image data ready and processed before final verification is needed, the system can quickly determine whether items were scanned without adding time to the checkout process, thus improving tracking reliability without increasing processing time.
Solution Approach 2:
The system skips detailed analysis of items that are clearly visible and identifiable in the captured images. By using quick visual recognition to confirm item presence and characteristics, the system maintains reliable item tracking while minimizing the time required for processing, avoiding unnecessary delays in the checkout process.
Data Source
AI summary
In some embodiments, apparatuses and methods are provided herein useful to detecting a mis-scan of an item. In some embodiments, there is provided a system for detecting a mis-scan of an item for purchase comprising a checkout station; a first staging location; a second staging location; a first area of interest at the checkout station; a second area of interest at the checkout station; a camera; and a control circuit configured to: receive an identifier of a first item; detect a hand of a user purchasing the first item, the first item, and a scanner on a first image captured by the camera; in response to the detection of the hand, the first item, and the scanner, initiate detection of mis-scan items during a checkout process; determine that a payment transaction has been received; and stop the detection of mis-scan items.