How Do Barcode Scanners Work?

You see barcodes everywhere. From chocolate bar labels to airline boarding passes to the stickers on delivery packages, barcodes bridge the gap between physical items and digital systems.

They also form the foundation for a surprisingly complex set of barcode scanning processes that begin with a human scanning a label.

This guide explains how barcode scanners work, from the scanning process to the technical elements of a barcode to the common reasons why a scanner won't function correctly.

A barcode scanner works by using a sensor to detect differences in light intensity between a barcode's black and white sections, and then converts these differences into electrical signals that can be processed by a higher-level application.

Each type of barcode scanner captures and processes label data differently, but they usually follow these steps:

1. Initial capture: The scanner’s sensor captures the barcode’s light and dark patterns, much like taking a photo. Laser scanners and charge-coupled device (CCD) readers emit light and capture reflections. Camera-based scanners capture the existing light entering their lenses.
2. Signal conversion: The scanning device’s sensor transforms light into electronic information through the photoelectric effect. The scanner’s light sensor or camera generates different electrical currents based on the intensity of reflected light it receives. These currents correspond to the barcode’s pattern.
3. Digital decoding/image processing: The electrical currents are converted into digital form to create a binary representation of the barcode’s pattern. Just as a human interpreter needs to understand a language to translate it, the processing method must understand the barcode’s standard to interpret the patterns it receives accurately.
4. Data processing and display: The binary data is transformed into user-facing formats, such as a device’s display or ERP database.

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More advanced barcode scanning technologies build on these steps to add value to users. For example, Scandit software employs Smart Label Capture (shown in video below) to give users only the data they need from complex labels with multiple barcodes and text fields — such as labels containing serial numbers, weights, or expiry dates. This avoids giving users extraneous information and having to scan different types of data separately.

How does user experience affect barcode scanning?

In addition to the technical aspects of how barcode scanners work, user experience also significantly influences the overall scanning workflow. The following image illustrates barcode scanning from the user’s perspective, including aiming their device, barcode capture, and viewing results. Inefficiencies and inaccuracies at any step can cause significant user delays and frustrations – especially in high-volume scanning environments.

What does AI do in a barcode scanner?

An AI-powered barcode scanner works by supplementing the traditional barcode capture and decoding process with machine learning techniques that enable a broader awareness of the scanner's environment and the user's intent.

This "contextual intelligence" allows barcode scanners to get more information about what the sensor sees and what the user wants to do. This enables features such as automatically scanning the correct barcode in environments crowded with barcodes and activating text recognition as a backup when a barcode's data cannot be read.

The three levels of AI-powered barcode scanners are:

• Level 1: AI in name only, usually a marketing label applied to basic computer vision techniques.
• Level 2: Tackles real-world complexity, such as low-light conditions and damaged barcodes.
• Level 3: Context-aware scanning, such as automatically picking the right barcode to scan.

Each type of barcode scanner has advantages and limitations, depending on where and how they are used.

Here are the most common types of barcode scanners used in enterprise applications.

Pen wands

When drawn across a barcode, a pen wand detects changes in reflected light as it moves over the dark and light areas. Since they need close contact with labels, pen wands are best suited for low-speed, low-volume scanning, as scans require more effort from users.

Laser scanners

Laser scanners sweep multiple laser beams across barcodes to detect changes in reflected light. Modern laser scanners often feature multi-line or omnidirectional scanning patterns to read barcodes in various orientations. They are ideal for higher scanning volumes but require precise aiming of labels one by one, and can get confused by glare and reflective surfaces. They also tend to be bulky and offer fewer features compared to other scanner types.

Charge-coupled device (CCD) readers

A CCD scanner, also known as an LED scanner, captures an electronic image of the barcode and analyzes it using software. They tend to be physically durable, but their narrow capture range means users spend more time scanning.

Camera-based scanners

Camera-based scanners read barcodes using digital image sensors (such as smartphone cameras, tablets, handheld computers, and drones), and image processing software. They tend to support the widest range of barcode types and adapt well to many situations, including low-light environments, damaged barcodes, and awkward scan angles.

When running on smart devices, the additional processing power enables capabilities such as scanning multiple barcodes at once and augmented reality (AR) overlays to guide users in ways other scanner types cannot (as shown by the AR example below).

Barcode scanners don't work when the device hardware or software cannot compensate for degradations in the barcode label, the scanning environment, or user behavior.

The following outlines six main reasons why barcode scanners may not function correctly.

Lack of symbology support

When a barcode scanner encounters an unsupported barcode type, users must resort to manual data entry, which can cause delays and errors.

To avoid this issue, you should validate any scanning solution against all the barcode symbology requirements for your business. Ideally, your solution supports a wider range of symbologies so you don’t run into issues if your business adopts them later.

Degradations due to environmental conditions

The physical environment in which scanning occurs can significantly affect a barcode scanner’s performance. Warehouses can subject scanners to low-light and high-glare situations. Retail stores must contend with varying humidity levels and occasional impacts from drops or mishandling.

These factors can reduce scanner lifespan, increase maintenance costs, and cause scanning failures that frustrate users and slow operations. Your barcode scanner implementation must account for these conditions through appropriate hardware selection and software that can adapt to them.

Poor scanning performance

Multiple interconnected factors affect barcode scanner performance. Scan speed and accuracy vary widely depending on barcode quality, quantity, distance, angle, and environmental conditions. User experience also matters, as the more difficult it is to find and scan a label, the longer the process takes. When scanners cannot read barcodes on the first try, workers must spend additional time repositioning items or attempting multiple scans.

Many barcode scanning solutions employ software-based measures to overcome these issues, such as allowing wider scan angles and longer scanning distances or employing performance optimization techniques.

For example, if workers are scanning one barcode while others are in view, techniques such as AI-powered context-based scanning (see video below) help them capture the right one.

Connectivity issues

Some scanning solutions rely heavily on network connectivity to function effectively – including sending label data off the device for processing. When connections become unstable or fail, such as last-mile delivery in a remote location, workflows can grind to a halt.

Barcode scanners that support offline operation are best able to solve this problem. There are many approaches to this, from storing captured data until connectivity is reestablished with a cloud processor to performing all decoding and processing on-device. The latter approach has the added benefits of uninterrupted scanning workflows and improved security as it prevents data from being transmitted off the device.

User experience struggles

Scanning performance depends just as much on the scanner’s ease of use as on its processing algorithms. User adoption rates also depend on how frustrated users are with the scanner’s interface.

If the barcode scanner isn't designed with humans in mind and doesn't include tools for developers to improve the user experience, workers will struggle with poor ergonomics and unintuitive controls – leading to frustration and slower workflows.

Choosing barcode scanning solutions that prioritize user-centered design helps overcome user experience and adoption issues. The image below shows Scandit SparkScan, a pre-built barcode scanning component with an interface that floats on top of any existing app. It gives users a powerful AI scanning engine within a UI that's efficient and comfortable from any device angle.

Integration problems

Integrating barcode scanning systems with existing business software can pose technical challenges. Legacy scanners may use incompatible data formats or lack modern APIs for real-time data exchange. Open-source solutions may not support the development frameworks your team uses or may lack the documentation and professional support necessary to run smoothly under high-volume workloads.

Integration challenges can lead to delayed deployment, data errors, and increased support costs. You can avoid these problems by working with barcode scanner providers who understand the realities of enterprise environments and offer support to get scanning deployed quickly and correctly.

To learn more about these common issues and others, read our blog on how to solve common barcode scanning challenges.

Scandit’s AI-powered camera-based scanning solutions are purpose-built to overcome many common pain points associated with barcode scanning: performance, usability, and integration effort.

Scandit’s SDKs include these features that improve barcode scanning performance and reduce deployment effort:

• Advanced AI, computer vision algorithms, and user-focused design that ensure the right items are captured and tracked accurately under real-world conditions. Accessed via SparkScan or Barcode Capture.
• Simultaneous scanning of multiple barcodes with MatrixScan.
• Instant identification of correct items via augmented reality (AR) with MatrixScan Find.
• No-code deployment of simultaneous barcode and text capture with Scandit Express.

To learn more about these and other barcode scanning solutions, read our barcode scanning product brochure, including options for no-code, pre-built, and custom deployments.

Our technology is easy to test for yourself with full-featured free trials and simple, fast and free demo apps.