Automated Price Tag Detection Using Image Analysis
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Solution Overview
Problem
Manual inspection of price tag labels and products at product storage facilities is time-consuming and increases operational costs, as workers could be performing other tasks if they were not involved in manually inspecting the product storage areas, price tag labels, and products.
Innovation Solution
An image capture device captures images of product storage structures, and a computing device analyzes these images to detect individual price tag labels and products, defining separate product storage spaces and associating price tag labels with respective products stored in those spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to associate price tag labels with products, then accuracy of label-product association is improved, but time consumption and operational cost increase
Solution Approach 1:
The patent replaces the manual mechanical inspection system with an automated image processing system. Image capture devices take photographs of product storage areas, and software algorithms automatically detect price tag labels, identify products, and associate them with each other, eliminating the need for manual visual inspection while maintaining association accuracy.
Solution Approach 2:
The system creates digital copies (images) of the physical product storage areas. These image copies are then processed by software to extract information about price tags and products, allowing virtual analysis and association without physical manual inspection, thus saving time while preserving accuracy.
2Measurement precision
If manual inspection is used to verify price tag labels and products, then label-product association accuracy is improved, but operational cost increases
Solution Approach 1:
The patent substitutes human workers with an automated system consisting of image capture devices and processing software. This replacement eliminates the need for workers to perform manual inspection tasks, thereby reducing operational costs related to labor while maintaining the ability to accurately associate price tags with products.
Solution Approach 2:
The system enables self-service automation where the image processing software independently performs the entire workflow of detecting price tags, identifying products, and making associations without human intervention. This autonomous operation improves productivity by freeing workers from repetitive inspection tasks.
3Loss of time
If automated image processing is used to detect price tag labels and products, then time consumption is reduced, but system complexity increases
Solution Approach 1:
The image processing system is designed to perform multiple functions: capturing images, detecting price tag labels, identifying products, and associating them with each other. This multi-functional approach consolidates what would otherwise require multiple separate systems into one integrated solution, managing complexity while achieving significant time savings.
4Reliability
If workers manually inspect product storage areas, then label-product association is verified, but productivity of other tasks decreases
Solution Approach 1:
The automated system performs inventory verification independently without requiring worker involvement. This self-service capability ensures reliable label-product association verification while simultaneously freeing workers to focus on higher-value tasks, thereby improving both reliability and overall productivity.
Data Source
AI summary
Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.