Automated Sell-By Date Recognition Using Time-Series Image Analysis
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Solution Overview
Problem
In retail environments, there is a need to efficiently recognize the sell-by dates of products on display, particularly for items like fresh foods and household goods that may not have labels, as existing methods are time-consuming and inefficient.
Innovation Solution
A processing apparatus and method that acquires time-series images of display areas, detects products, determines their identity, manages display times, and outputs information related to the sell-by dates, using a combination of product detection and identity determination units to automate the tracking and reporting of product freshness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual checking of labels on each product is performed, then sell-by date information can be obtained, but the process becomes very time-consuming
Solution Approach 1:
The patent replaces the manual mechanical checking process with an automated image recognition system. The system uses imaging devices to capture product images and automatically extracts sell-by date information through OCR (optical character recognition) and image processing algorithms, eliminating the need for manual label checking while maintaining accurate date recognition.
Solution Approach 2:
The system enables products to 'self-report' their sell-by dates through visible labels or markings that can be automatically read. The imaging system captures images of products on shelves, and the processing unit automatically extracts date information without requiring human intervention, allowing the product information to serve itself for inventory management purposes.
2Loss of information
If labels are attached to each product for tracking, then sell-by date information can be captured, but products like fresh foods and side dishes cannot have labels attached
Solution Approach 1:
The patent creates a universal system that can handle both labeled and unlabeled products. The image recognition system can extract sell-by date information from various sources: printed labels on packaged goods, markings on fresh produce, or even handwritten dates. This multi-functional approach allows the same system to serve diverse product types including packaged foods, fresh produce, and unpackaged items without requiring different solutions.
Solution Approach 2:
The system adapts to different product types by changing its detection parameters and methods. For labeled products, it uses OCR to read printed text; for fresh foods without labels, it may recognize handwritten markings or use alternative identification methods. The processing unit dynamically adjusts its approach based on the product characteristics, enabling versatile application across different product categories.
3Productivity
If automated image recognition is implemented, then time consumption is reduced, but the system complexity increases
Solution Approach 1:
The patent divides the complex task of sell-by date recognition into separate functional modules: an imaging device for capturing images, a processing unit for image analysis and date extraction, and a database for storing results. This segmentation allows each component to perform its specific function efficiently, reducing overall system complexity while maintaining high productivity. The modular architecture makes the system easier to implement and maintain compared to a monolithic approach.
Data Source
AI summary
The present invention provides a processing apparatus (10) including: an acquisition unit (11) that acquires a plurality of time-series images including a display area; a product detection unit (12) that detects a product from each of a plurality of the time-series images; an identity determination unit (13) that determines identity of products detected from the images that are different from each other; a display time management unit (14) that manages a display time of each detected product, based on a result of the detection and a result of the identity determination; and an output unit (15) that outputs information related to the display time of each detected product.