Automate inventory monitoring, product recognition, and self-checkout processes – for greater efficiency and an improved shopping experience. Freely programmable or available as a ready-to-use solution.
Machine Vision for Retail
Typical Challenges in Retail
01
Reliable Product and Inventory Monitoring
Products, shelves, and inventory levels must be continuously monitored to detect stock shortages at an early stage.
02
Managing High Product Variety
Different packaging types, product sizes, seasonal items, and promotional packaging make reliable product recognition challenging.
03
Optimizing Processes and Customer Experience
Self-checkout, shelf availability, and space utilization require automated and reliable analysis.
04
Reducing Losses and Errors
Inventory discrepancies, misplaced products, and shrinkage must be detected early to reduce costs.
Our Approaches
Two Paths to the Right Vision Solution
Depending on your integration requirements and project timeline, IMAGO offers two distinct approaches recycling applications.
Open Plattform
Flexible Vision Platform
For retail technology providers, and retailers who require full control over application logic, integration, and scalability.
- Freely programmable with the IMAGO ViewIT software framework, C++, Python, and HALCON – no black box, full control
- Multiple vision tasks on a single device – from product recognition and inventory monitoring to self-checkout applications
- Portable across all IMAGO devices, with OPC UA and REST connectivity for Industry 4.0 integration
- Long-term availability, including ODM (Original Design Manufacturer) variants for serial machine production
Ready to use
Preconfigured Solution
For users with a specific inspection challenge who need fast and reliable results without extensive in-house development.
- Deep-learning inspection of visually variable parcels and logistics objects without programming using a web-based GUI
- Fast deployment with minimal lead time and a clear focus on rapid time-to-market
- Reliably detects product variations, misplaced items, and visual anomalies in retail environments
- Consulting and support from the experienced IMAGO engineering team – robust hardware made in Germany
Decision Guide
What Is Your Goal?
Choose the approach that best fits your project – both lead to a reliable inspection solution.
Maximum Flexibility
You develop your own retail applications or integrate machine vision into existing checkout, inventory, or store management systems.
Fast Implementation
You have a specific task – such as product recognition or anomaly detection – and need a ready-to-use system quickly.
Differentiation
Why IMAGO for Retail?
Hardware, software, and system integration work together to enable reliable automation and intelligent analysis in retail environments.
Open Software Framework
Freely programmable instead of a black box – full control over every inspection task on the line.
Multiple Tasks, One System
OCR, code reading, quality control, and AI inspection run on the same hardware instead of multiple systems.
Long-Term Availability
ODM variants and long product life cycles for serial machines and global rollouts.
Future-Proof Architecture
Scalable platform without vendor lock-in that grows with your requirements.
High-Speed-Vision
Hundreds of products per minute with processing power directly in the camera or box PC.
Applications
Typical Applications in Retail
IMAGO vision systems support these four application areas in retail. This is only a small selection of what machine vision enables today.
Shelf and Inventory Monitoring
Products, shelves, and retail spaces are continuously monitored to detect stock shortages, misplaced items, and empty shelf spaces at an early stage.
Self-Checkout and Product Recognition
Products are reliably identified at self-checkout stations to speed up transactions and prevent scanning errors.
AI-Powered Theft Detection
Suspicious actions such as concealing products or rapidly clearing shelves are automatically detected to identify potential shoplifting at an early stage.
Customer Flow and Space Analysis
Customer traffic, movement patterns, and dwell areas are analyzed to reduce waiting times, optimize retail spaces, and improve the shopping experience.
Technology for Demanding Retail Applications
A powerful machine vision system for retail must reliably handle diverse products, changing assortments, and different analysis tasks. Products, packaging, and retail environments are constantly evolving, requiring flexible systems that can quickly adapt to new demands.
The combination of traditional machine vision and AI enables reliable product recognition, inventory monitoring, and automated self-checkout processes. At the same time, different applications – from product recognition to space utilization and customer flow analysis – can be implemented on a single technology platform.
Thanks to the open software framework, new store concepts, analysis methods, and AI models can be flexibly integrated. The future-proof architecture allows existing systems to be continuously expanded, providing a solid foundation for future retail applications.
Product recommendations
Recommended Solutions for Retail
The following systems are designed to meet the demands of modern retail applications. They combine compact design, AI-based processing, and intelligent analytics. Depending on the application, they can be freely programmed or deployed as ready-to-use solutions.
Reliably automate inventory monitoring, product recognition, and self-checkout processes.
Frequently Asked Questions
How reliably does the system recognize products, packaging, and product variants?
Packaging designs, promotional items, and product assortments are constantly changing in retail. AI-based machine vision recognizes products based on shape, color, logos, or packaging features and maintains reliable recognition even with new variants. This reduces errors at self-checkout stations and improves inventory data accuracy.
How can inventory levels and product movements be automatically tracked?
Machine vision automatically recognizes products on shelves, in displays, or at goods receiving areas. This enables early detection of inventory discrepancies and simplifies stocktaking. Thanks to the open platform, inventory management systems can be flexibly integrated to provide transparency into product availability and replenishment needs.
Is the platform scalable enough for future retail and AI applications?
Retail is continuously evolving towards automation and data-driven processes. An open vision platform enables the integration of new AI models, additional cameras, or new applications through software. This allows retailers and system providers to expand their solutions over the long term without having to replace their entire infrastructure.
