Mobile Image Capture for Price Tag–Product Pairing Verification
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Solution Overview
Problem
Manual inspection of price tag labels at product storage facilities is time-consuming and increases operational costs due to the large number of storage areas and products, necessitating a more efficient verification method.
Innovation Solution
An image capture device moves about the facility, capturing images of product storage structures, extracting characters from price tag labels and products, and correlating them with inventory data to verify proper allocations using a computing device and database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection of price tag labels is performed by workers, then verification accuracy is maintained, but time consumption and operational costs increase significantly
Solution Approach 1:
The patent replaces the mechanical manual inspection system with an automated image processing system. Image capture devices photograph price tag labels, and computer vision algorithms automatically extract and verify product information, substituting human visual inspection with optical-digital processing that achieves comparable accuracy without time loss.
Solution Approach 2:
The system creates digital copies of price tag labels through photography, then processes these copies through image recognition algorithms to extract product information. This copying approach allows parallel processing of multiple labels simultaneously, verifying accuracy while dramatically reducing the time required compared to sequential manual inspection.
2Reliability
If manual inspection is performed to ensure accurate price tag verification, then product labeling correctness is confirmed, but operational costs increase due to worker time
Solution Approach 1:
The patent substitutes expensive manual labor with automated image capture and processing equipment. The system uses cameras to photograph labels and algorithms to verify product information, eliminating the need to pay workers for inspection tasks while maintaining reliable verification of product labeling correctness.
Solution Approach 2:
The system enables self-service verification where the image processing system automatically extracts product information from labels and compares it against database records without human intervention. This automated self-verification process ensures labeling correctness while eliminating labor costs associated with manual inspection.
3Productivity
If the number of workers performing manual inspection is increased, then verification coverage improves, but operational costs and time consumption both increase
Solution Approach 1:
The automated image processing system serves multiple verification functions simultaneously - it can process numerous price tag labels in parallel, verify product information, check pricing accuracy, and generate reports all through a single unified system. This multi-functionality provides comprehensive verification coverage without the need to deploy multiple workers, reducing operational costs while improving productivity.
Solution Approach 2:
The system captures images of all price tag labels in the storage area and processes them all through automated recognition, performing more verifications than a single worker could manually complete. This excessive automated action ensures complete verification coverage across all products while maintaining cost efficiency through automation rather than proportional increases in labor.
Data Source
AI summary
Systems and methods of verifying pairings of price tag labels and products at a product storage facility include an image capture device that moves about and captures images of product storage structures at the product storage facility, and a database that stores inventory data associated with the products stocked at the product storage facility. A computing device processes the images to extract one or more characters from the price tag labels and products detected in the images, correlates the extracted characters to the inventory data to identify a product code and a product name that matches the characters extracted from the price tag labels and the products. If the characters extracted from the price tag and from the on-shelf product to which the price tag label is allocated match, the database is updated to reflect that the price tag label is properly allocated to the appropriate on-shelf product.