Shelf Support Detection Using Stitched Images for Inventory Audits
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Solution Overview
Problem
Manual inspection and identification of products on storage shelves in large retail facilities is labor-intensive and time-consuming, increasing operational costs.
Innovation Solution
An image capture device captures multiple images of product storage structures, which are stitched together to generate a composite image, and a computing device processes this image to detect vertical and horizontal support members using color distribution maps and positional coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to identify and count products on shelves, then workers can directly observe and record inventory information, but the process becomes very time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated image processing system. Image capture devices take photographs of shelves, and computer algorithms automatically identify and count products, substituting human visual inspection with computational analysis. This resolves the contradiction by maintaining accurate inventory identification while dramatically reducing inspection time.
Solution Approach 2:
The patent creates digital copies (images) of the physical shelf inventory and processes these copies computationally. Instead of workers directly observing physical shelves, the system captures images and analyzes them through algorithms that identify products, their positions, and quantities. This copying approach enables rapid automated analysis without the time constraints of manual inspection.
2Reliability
If workers manually inspect product display shelves to update inventory, then inventory information can be kept current, but operations cost significantly increases
Solution Approach 1:
The patent replaces expensive manual labor with automated image capture and processing systems. Image devices and computer algorithms perform inventory tracking without human workers, maintaining reliable inventory information while eliminating the significant operations costs associated with manual inspection teams.
Solution Approach 2:
The system enables inventory tracking to serve itself through automated image analysis. The image processing algorithms automatically identify products, update inventory records, and track changes without requiring human intervention. This self-service capability maintains accurate inventory information while eliminating ongoing labor costs.
3Reliability
If workers are deployed to manually inspect shelves, then inventory can be monitored, but these workers could be performing other tasks instead
Solution Approach 1:
The patent replaces workers engaged in inventory monitoring with automated image processing systems. This substitution frees workers to perform other value-added tasks that contribute to overall operational productivity, while the automated system maintains reliable inventory monitoring independently.
Data Source
AI summary
Systems and methods of detecting support members of product storage structures that store products at a product storage facility include an image capture device that captures images of a product storage structure including vertical and horizontal support members. A computing device including a control circuit is configured to: obtain the images of the product storage structure captured by the image capture device, stitch the obtained images together to generate a stitched image that depicts the product storage structure, generate a color distribution map of the stitched image of the product storage structure to detect individual ones of the horizontal and vertical support members of the product storage structure.