SKU Differentiation via Pixel-to-Physical Dimension Ratios
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Solution Overview
Problem
Existing image recognition techniques fail to distinguish between products that have similar appearances but vary in size, making it difficult to enforce planograms and manage inventory effectively in retail environments.
Innovation Solution
A system and method that uses an image recognition application to identify products, generate regions of interest, determine pixel and physical dimensions, calculate pixel-to-physical dimension ratios, and assign stock keeping unit identifiers based on these ratios, allowing for accurate differentiation of products with similar packaging but varying sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing image recognition techniques are used to identify products, then product identification can be performed, but products with similar appearances but different sizes cannot be distinguished
Solution Approach 1:
The patent transitions from two-dimensional image recognition to three-dimensional measurement by incorporating depth information through time-of-flight sensing. This allows the system to distinguish between products of similar appearance but different sizes by measuring their actual physical dimensions in addition to visual characteristics.
Solution Approach 2:
The system changes the measurement parameters from purely visual (2D) to include physical dimensions (3D). By adding depth measurement capability through time-of-flight sensors, the system can detect and differentiate products based on their actual size parameters, resolving the limitation of traditional image recognition.
2Productivity
If manual tracking of product location and quantity is performed, then inventory can be monitored, but the process is labor-intensive and difficult to enforce planograms
Solution Approach 1:
The system enables self-service inventory auditing by automatically capturing images and depth data, identifying products, measuring their dimensions, and comparing them against planogram requirements without human intervention. This eliminates the labor-intensive manual tracking process while maintaining accurate inventory monitoring.
Solution Approach 2:
The patent replaces manual mechanical inventory tracking with an automated optical and computational system. Image capture devices and depth sensors substitute for human eyes and hands, while image processing algorithms replace the cognitive and decision-making processes involved in manual planogram enforcement.
3Manufacturing precision
If image recognition is used without physical dimension measurement, then product identification is faster, but size variation among similar products cannot be detected
Solution Approach 1:
The patent introduces depth data as an intermediary measurement layer between the image capture device and the product identification system. This intermediary depth information serves as a bridge that enables size differentiation without requiring direct physical contact or complex measurement apparatus, simply by processing additional optical data.
Data Source
AI summary
The disclosure includes a system and method for distinguishing between stock keeping units of similar appearance that vary in size. An image recognition application receives an image including a shelving unit stocking a plurality of items, identifies each item in the image, generates a region of interest for each identified item in the image, identifies a physical dimension of a portion of region depicted in the image, determines a dimension of the region of interest for each identified item and the portion of region in pixels, determines a pixel-to-physical dimension ratio using the dimension in pixels of the portion of region and the physical dimension of the portion of region depicted in the image, and determines a stock keeping unit identifier of each identified item in the image based on the pixel-to-physical dimension ratio and the dimension of the region of interest for each identified item.