Image-Based Product Clustering for Automated Inventory Counting
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Solution Overview
Problem
Manual inventory inspection of products in large storage facilities is time-consuming and increases operational costs for retailers.
Innovation Solution
A system comprising an image capture device, control circuit, and database that automatically processes images to detect, cluster, and count products, updating inventory data based on textual, visual, and spatial similarities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to inventory products, then workers can identify stock levels, but the process becomes time-consuming and increases operational costs
Solution Approach 1:
The patent replaces the mechanical manual inspection system with an automated image processing system. Image capture devices photograph product shelves, and computer vision algorithms automatically detect, classify, and count products, eliminating the need for workers to physically inspect each item while maintaining inventory accuracy
Solution Approach 2:
The system creates visual copies (images) of the physical inventory and processes these copies digitally. Instead of workers directly observing and recording physical products, the system captures images and uses image analysis to extract inventory information, significantly reducing inspection time while preserving measurement precision
2Area of stationary object
If manual inspection is deployed across large storage facilities, then all product areas can be covered, but operational costs increase significantly
Solution Approach 1:
The automated image processing system serves multiple functions: it captures images of diverse products across various storage areas, automatically classifies different product types, counts inventory, and updates database records. This single multi-functional system replaces multiple workers who would each need to be trained for specific inspection tasks, reducing operational costs while maintaining broad coverage
Solution Approach 2:
The system enables self-service inventory management where the imaging and processing system automatically performs all inspection tasks without human intervention. The computer vision algorithms autonomously detect products, classify them by type and orientation, count quantities, and update databases, eliminating the need for paid manual labor while covering extensive storage areas
3Loss of information
If workers are assigned to manual inspection tasks, then inventory data can be collected, but other productive tasks are delayed
Solution Approach 1:
The patent replaces human workers with an automated image processing system that continuously captures and processes inventory images. This substitution ensures uninterrupted inventory data collection while freeing workers to perform value-added tasks such as product replenishment, shelf organization, and customer service, thereby increasing overall operational productivity
Solution Approach 2:
The automated system enables continuous inventory monitoring through ongoing image capture and processing. Unlike manual inspection which occurs periodically when workers are available, the automated system operates continuously or on-demand without interrupting other operations, ensuring timely inventory data collection while maintaining high overall productivity
Data Source
AI summary
In some embodiments, apparatuses and methods are provided herein useful to updating inventory of products. In some embodiments, there is provided a system for updating inventory of products including a database; at least one image capture device; and a control circuit. The control circuit is configured to: process an image by: detecting units of one or more products in the image; grouping each detected unit into one or more clusters based on at least one of textual similarities, visual similarities, geometrical similarities, or relative spatial distance; detecting a product identifier for each cluster; identifying a product corresponding to the detected product identifier of each cluster; and counting the detected units associated with each cluster. The control circuit is configured to cause an update to the inventory of products in the database based on the counted detected units of each cluster.