Image-Based Commodity Recognition for Retail POS Systems
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Solution Overview
Problem
In retail environments, especially in supermarkets and pastry shops, existing commodity code reading systems require pre-affixed barcodes or QR codes on packages, which is impractical for perishable items like buns and doughnuts, leading to inefficiencies in sales registration and inventory management.
Innovation Solution
A store system that includes an image pickup section, object recognition, and a problem-solving mechanism, allowing for image-based recognition of commodities without pre-affixed codes, using a POS terminal and commodity reading apparatus to capture images, recognize objects, and perform sales registration by comparing features like surface state and similarity thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If code symbols are affixed to packages for commodity identification, then sales registration accuracy is improved, but preparation time and complexity increase for perishable items
Solution Approach 1:
The patent extracts the code symbol from the package and places it on the commodity itself. This allows the commodity to be identified directly without requiring separate packaging with affixed codes, eliminating the time-consuming package preparation step while maintaining identification accuracy.
Solution Approach 2:
The patent uses image pickup apparatus to capture visual information of the commodity and creates a digital copy for identification. This optical copying method replaces the physical code symbol affixing process, enabling quick identification without manual package preparation.
2Measurement precision
If code symbols are affixed to each commodity package, then individual item tracking is improved, but labor and material costs increase
Solution Approach 1:
The patent removes the requirement for physical code symbols and their affixing process entirely. Instead, it extracts visual features directly from the commodity appearance, eliminating labor and material costs associated with code symbol application while maintaining individual item tracking capability.
Solution Approach 2:
The patent replaces the mechanical process of affixing code symbols with an optical imaging system. The image pickup apparatus captures commodity images, and image processing algorithms automatically extract identification features, substituting manual or automated code application with a non-contact optical system that reduces labor and material requirements.
3Device complexity
If manual code reading is used for sales registration, then system simplicity is maintained, but processing speed decreases
Solution Approach 1:
The patent uses optical copying through image pickup to capture commodity information, which is then processed automatically. This maintains relative system simplicity while dramatically increasing processing speed compared to manual code reading, as the image capture and recognition process occurs rapidly without manual intervention.
Solution Approach 2:
The patent replaces manual code reading operations with automated image-based recognition. The image pickup apparatus and image processing system automatically capture and analyze commodity information, substituting slow manual scanning with fast optical capture and automated recognition, thereby increasing sales registration speed while keeping the system relatively simple.
Data Source
AI summary
According to one embodiment, a store system includes: an image output section configured to output an image picked up by an image pickup section; an object recognizing section configured to recognize a specific object by reading a feature value of the output image; a check-image display section configured to display, on a display section, at least an image concerning the recognized object; and a problem solving section configured to receive, when there is a problem in the recognition of the object, an instruction indicating the problem and solve the problem according to content of the received instruction.