Digital Watermark Product Identification via Multi-Angle Imaging
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Solution Overview
Problem
Current supermarket checkout systems face challenges in efficiently reading barcodes due to difficulties in locating and positioning barcodes on products, especially with irregularly shaped items, and issues with radio-frequency identification (RFID) tags, which are costly and prone to privacy concerns, as well as limitations in existing technologies for accurately identifying products at self-service checkout stations.
Innovation Solution
The implementation of a digital watermark on product packaging that can be sensed from multiple angles using fixed cameras, combined with various recognition technologies such as structure-from-motion, structured light scanning, and plenoptic cameras, to identify products by analyzing 2D and 3D imagery, and providing a confidence score for accurate identification, while also considering data from the store aisle and shopper interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If barcodes are used for product identification, then checkout speed is improved, but difficulty in locating and positioning barcodes on irregularly shaped items increases
Solution Approach 1:
The patent uses digital watermarking technology to embed product identification information directly into the product packaging images themselves, rather than relying on separate barcode labels. This allows the identification data to be copied into the visual structure of the packaging, making it inherently integrated with the product appearance and eliminating the need for separate barcode location and positioning steps
Solution Approach 2:
The patent combines product identification information with the visual packaging design by embedding watermarks directly into the packaging images. This merges the identification function with the packaging structure itself, so that the product image serves dual purposes: both visual appeal and identification, eliminating the need for separate barcode elements
2Measurement precision
If RFID tags are used for product identification, then checkout accuracy is improved, but cost increases
Solution Approach 1:
The patent replaces expensive RFID tags with digital watermarking technology that uses standard imaging cameras and software-based identification. The watermarking approach uses inexpensive digital information embedded in the packaging design rather than costly electronic components, achieving comparable identification accuracy at a fraction of the cost
Solution Approach 2:
The patent replaces the electromagnetic RFID system with an optical imaging and digital processing system. Instead of using radio frequency tags and readers, the system uses standard cameras to capture packaging images and software algorithms to extract identification information from digital watermarks, substituting a mechanical/optical system for an electromagnetic one
3Measurement precision
If multiple cameras and scanning technologies are used, then product identification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes the imaging system multi-functional by using standard cameras to perform both traditional barcode scanning and digital watermark detection. The same camera hardware serves multiple identification purposes, and the software system can handle different identification methods (barcodes, watermarks, image recognition) through a unified processing framework, reducing the need for separate specialized devices
Solution Approach 2:
The patent introduces digital watermarking as an intermediary layer between the product packaging and the identification system. The watermarks serve as a universal interface that can be detected by standard cameras, bridging the gap between simple imaging hardware and accurate product identification without requiring complex specialized scanning equipment
Data Source
AI summary
In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. Logos may be identified and used—or ignored—in product identification. A great variety of other features and arrangements are also detailed.