The Many Eyes of Retail Computer Vision - And Why Stores Need Them All

Retail is a busy environment. Products come and go. Shelves are restocked and emptied throughout the day. Employees work hard to keep inventory moving, customers satisfied, and the store operating smoothly. At the heart of all this is one key need: having clear, accurate information exactly when it’s needed. In other words, visibility.

Enter retail computer vision - the technology that helps stores truly see what’s happening.

What is retail computer vision?

Retail computer vision uses cameras and AI to understand what is happening in a store by visually observing it. Single-image captures and video sequences of barcodes, products, and text from different cameras, such as smart devices and fixed-position cameras, are transformed into data that allows retailers to see shelves, products, and labels, not just monitor transactions.

Retail computer vision converts physical store activity into digital data to improve visibility and decision-making. It turns smart devices into powerful retail tools. Helping workers see more and act faster.

Not all retail computer vision works the same way

You can think of it like a set of tools, each designed for a specific job or challenge in retail. Scandit uses computer vision across its platform in this way.

Let’s look at the most common uses and how they benefit retailers.

Barcode capture

Retail runs on barcodes. But slow, inaccurate scanning can lead to inefficiencies and operational issues.

Using a smart device camera, Scandit applies machine learning to detect barcodes in images. We train our models to recognize codes in many different settings. Once a barcode is found, computer vision decodes it. Even if there are multiple codes, the barcode is damaged, very small, or has glare, our advanced algorithms can handle these challenges.

And capturing barcodes on a smart device this way enables immediate task visibility. Real-time feedback and AR overlays guide associates on their next-best actions.

This means fewer errors and faster workflows. Perfect for order fulfillment and managing inventory.

Text capture

Not everything is included in a barcode. Dates, weights, price tags, and serial numbers are all needed for operational visibility.

Scandit’s Smart Label Capture tool collects this information along with barcodes. It uses computer vision, optical character recognition (OCR), and AI to extract and analyze label data in many different formats.

It understands the structure of barcodes and text (e.g., an IMEI number is always a sequence of 15 decimal digits), the relative position of fields, and the context of elements close to each other (e.g., “BEST BEFORE” next to an expiry date).

This accelerates data entry and eliminates manual errors, like entering the wrong weight or expiration date, preventing revenue loss and customer dissatisfaction.

Object recognition

Arguably, the biggest blind spot in a store is what’s actually on shelves. Shelves are complex, products look alike, and stock gaps go unnoticed.

Our shelf intelligence solution, ShelfView, uses advanced computer vision and machine learning to capture images of store shelves and generate actionable insights. Simply put, it lets retailers see what is really on the shelf, not just what their inventory system says.

Images are captured using smart devices, fixed-position cameras, and robots and then processed:

• Scene parsing identifies trays, shelves, products, and shelf labels.
• Products are identified down to the SKU level with image recognition.
• OCR and barcode scanning are used on shelf labels to extract product and price information.

Together, they create a precise digital representation of the shelf (often called a realogram).

Associates then receive prioritized alerts for missing or misplaced products, pricing, and promotional errors, so issues can be resolved before customers notice them.

ID scanning and verification

Selling age-restricted goods carries some risk. Fines and license revocation may occur if age and authentication checks aren't carried out, and minors receive goods.

Eyeballing an ID to determine age takes time. Detecting a fake ID is nearly impossible.

Scandit uses computer vision to perform secure ID validation checks on the device for fast, accurate authentication. It works in 3 steps:

1. The camera captures a usable image from a video feed.
2. It understands the document. Computer vision identifies the ID type and key areas, such as photos, text fields, and barcodes, instantly and on-device, ensuring data protection.
3. It analyzes authenticity. ID Validate uses computer vision models to inspect hundreds of visual characteristics. These include fonts, spacing, alignment, print quality, and format patterns.

The system looks for inconsistencies that are invisible to the human eye but common in fake IDs. It also cross-checks data. The system compares the information printed on the ID with the information encoded digitally. Mismatches raise flags.

Finally, it delivers a simple result to the user: authentic or not.

This helps retailers reduce fraud, save time, and protect their business and reputation.

The power of combining retail computer vision tools

One tool is good. Many together are better. Order fulfillment is a great example of a workflow that relies on all the tools combined.

• Object recognition plugs shelf gaps.
• Barcode scanning tracks the item.
• Label capture enters the correct weight and price.
• ID verification ensures a compliant handover.

What might seem like a complex, experimental, or even futuristic technology with limited applications is, in reality, already commonplace.

Retail changes fast, and retailers need visibility. With Scandit, you see more. You know more. You act faster.

FAQs

What is retail computer vision?

Retail computer vision uses AI and cameras to understand what’s happening in a store. It turns images of shelves, products, and labels into real-time data that improves visibility, accuracy, and decision-making.

How is retail computer vision used in stores?

Retailers use computer vision for barcode scanning, shelf monitoring, label and text capture, and ID verification. These capabilities help teams restock faster, reduce errors, stay compliant, and serve customers more efficiently.

Why is retail computer vision important for modern retail?

Retail operations change constantly throughout the day. Retail computer vision provides real-time visibility across shelves and workflows, helping retailers act faster, maintain accuracy, and operate efficiently even with tight labor and high complexity.