Automate Visual Testing With Selenium

Top 6 Automated Visual Testing Tools for Selenium in 2026

Testers who are new in their journey to automated software testing must be familiar with Selenium, which has grown to be a global favourite for automating tests across production.

In fact, Selenium shows no signs of slowing down, powering web test automation for over 70% of teams and appearing in the majority of automation job listings for 2025-2026.

As UI complexity increases, teams are increasingly extending Selenium beyond functional checks into automated visual testing. Visual testing focuses on how an application looks to end users, verifying that layouts, components, text, and styling render correctly across browsers, devices, and screen sizes.

With this article, we’re diving into the best automated visual testing tools for selenium integrations, how each of them differs, and how to pick the right tool that aligns with your unique testing specifications.

What is Automated Visual Testing?

Automated visual testing is a testing approach that validates how an application looks after every code change, not just how it behaves. Instead of checking logic or functionality, it captures screenshots of pages or components and compares them against approved baseline images to detect unintended visual changes.

These visual UI testing helps catch issues like misaligned elements, broken layouts, missing text, color shifts, or font changes, problems that functional tests often miss because the code still works. By automating this process, teams can consistently validate visual correctness across browsers, screen sizes, and devices without relying on time-consuming manual checks.

Automated visual testing typically runs as part of CI/CD pipelines. This means visual regressions are detected early, reviewed alongside code changes, and resolved before they reach production, keeping the user experience stable as releases move faster.

Why Selenium Alone Isn’t Enough for Automated Visual Testing

Selenium can be used for visual testing, but the challenge isn’t capability—it’s reliability and scale. As visual coverage grows, teams start running into practical limitations that make pure Selenium-based visual checks hard to sustain.

• Baseline Maintenance Quickly Becomes Painful: With Selenium, teams must manually capture, store, and version baseline screenshots for every UI state. As designs evolve, updating and managing these “golden images” turns into ongoing maintenance work rather than a one-time setup.
• Minor Rendering Differences Create Noise: Small variations like font rendering, anti-aliasing, subpixel shifts, or OS-level differences often trigger failures, even when the UI looks perfectly fine. Without intelligent diffing, teams spend more time reviewing false positives than real issues.
• Cross-Browser Visual Testing Multiplies Complexity: Validating visuals across Chrome, Firefox, Safari, and Edge means maintaining separate baselines for each browser. As browser coverage expands, baseline sprawl and comparison inconsistencies grow exponentially.
• No Built-In Review or Collaboration Workflow: Visual diffs generated through Selenium typically live in local files or CI logs. There’s no centralized place for teams to review changes, leave comments, or approve intentional UI updates together.

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6 Automated Visual Testing Tools for 2026

Visual regression testing has matured in recent years, with solutions ranging from full-featured AI-powered platforms to lightweight open-source utilities. Some tools focus on extensive cross-browser and device coverage, while others integrate directly into test frameworks for quick baseline comparisons.

Below, we cover six tools that are shaping visual testing workflows in 2026:

1. BrowserStack Percy

Percy is an AI-powered automated visual testing software that helps teams catch unintended UI differences early in the development cycle. Percy brings next-generation AI visual engine and AI reviews proactively trying to reduce false positives and flaky tests derived from dynamic UI content.

Percy has a dedicated platform called App Percy for mobile visual testing, bringing a host of iOS and Android devices to cross-test your application across different device and browser combinations.

It integrates directly with popular CI/CD tools and test frameworks to capture snapshots on every build, compare them against baselines, and highlight meaningful changes.

Key features of Percy:

Pricing: You can create an account on Percy for free, with its free inclusions offering up to 5000 screenshot uploads per month. For more screenshot uploads, further testing capabilities, and mobile device coverage you can switch to paid options starting from $199 per month.

Thinking about switching to visual automation?

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• AI Reviews
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2. Applitools Eyes

Applitools Eyes is an advanced AI-powered visual testing platform that uses machine learning to detect meaningful UI changes across browsers, devices, and viewports. It integrates with over 50 test frameworks, including Selenium, Cypress, and Playwright to bring intelligent visual validation into existing test workflows.

Key Features of Applitools Eyes:

• Visual AI Detection: Uses computer-vision algorithms to filter out insignificant differences and focus on real UI regressions.
• Ultrafast Cross-Browser Testing: Executes visual comparisons across multiple browsers and viewports via its Ultrafast Grid.
• Smart Maintenance & Root Cause Analysis: Automatically groups similar changes and helps pinpoint defects quickly.

Major Drawbacks:

• High Cost Barrier: Licensing starts around $899-$969 per month for paid tiers, making it expensive for many teams.
• Learning Curve: AI-driven features and setup can take time to configure effectively, especially for dynamic content.
• Cloud Dependency: Primarily a SaaS offering, which can be limiting for offline or highly restricted network environments.
• Complex Pricing Negotiations: Pricing may require sales engagement and custom terms, which slows procurement.

Pricing: Applitools Eyes offers a free tier (with limited pages or component checkpoints) as well as paid plans. Starter plans typically begin around $899–$969 per month (billed annually) for broader visual testing capacity, with enterprise options available for custom usage, extended retention, and enhanced support.

3. Galen Framework

Galen Framework is an open-source layout and responsive design testing tool built on Selenium. It uses a domain-specific language called Galen Specs to describe UI layouts and ensure element positions, alignments, and proportions meet design expectations. Tests can be run against different screen sizes and browser configurations.

Key Features of Galen Framework:

• Responsive Layout Validation: Validates element positioning and alignment across multiple viewport sizes.
• Selenium Integration: Works with Selenium Grid and popular browser drivers for broad test execution.
• Rich Reporting: Generates detailed HTML reports with highlighted layout deviations.

Major Drawbacks:

• Not Full Visual Regression: Focuses on layout specs and alignment, not pixel-level visual differences.
• Specialized Syntax: Requires learning Galen Specs language for defining layout rules.
• Limited Dynamic Content Handling: Not designed to intelligently filter runtime changes or dynamic elements.
• Less Intuitive UI: Lacks modern dashboards or collaborative review features common in newer visual tools.

Pricing: Galen Framework is completely free and open-source under the Apache 2.0 license, with no paid tiers.

4. Needle

Needle is a lightweight Python-based visual testing library that integrates with Selenium and captures screenshots to detect UI regressions. It’s ideal for quick baseline comparisons and simple visual checks in Python automation projects.

Key Features of Needle:

• Selenium Screenshot Comparison: Captures and compares screenshots of page portions or full pages.
• CSS & Layout Validation: Helps verify CSS rendering and element positioning.
• Custom Viewport Support: Allows testing across defined viewport sizes.

Major Drawbacks:

• No Advanced Diff Intelligence: Lacks perceptual or AI-based visual filtering.
• Limited Scope: Best suited for simple visual checks, not deep cross-device regression.
• Minimal Collaboration: No built-in review dashboard or team workflows.
• Community Support Only: Relies on community maintenance, which may be inconsistent.

Pricing: Needle is free and open-source with no commercial pricing.

5. AShot

AShot is an open-source Java library designed to capture element-level and full-page screenshots within Selenium tests. It supports advanced features like image stitching and precise diff highlighting, making it useful for Java teams needing granular visual comparisons.

Key Features of AShot:

• Element & Full-Page Screenshots: Captures deep UI snapshots at element or page scale.
• Image Stitching: Combines multiple captures for seamless full-page visuals.
• Detailed Difference Highlighting: Emphasizes pixel differences for exact regression points.

Major Limitations:

• No AI or Noise Filtering: Pixel differences can be noisy without intelligence.
• Selenium Dependency Only: Works within Selenium and lacks standalone visual workflows.
• Limited Browser Coverage: Requires custom setups for broad cross-browser execution.
• No Review Interface: Does not include a built-in diff review or collaboration UI.

Pricing: AShot is free and open-source with no paid tiers.

6. SeleniumBase

SeleniumBase is an open-source Python framework that extends Selenium with simplified syntax and additional utilities. While not strictly a visual testing tool, it supports screenshot capture and comparison routines that teams can use for basic visual regression tests within Python workflows.

Key Features of SeleniumBase:

• Simplified Selenium Commands: Makes test writing faster and cleaner.
• Screenshot Support: Enables capturing and comparing screenshots within tests.
• Built-In Test Utilities: Includes assertions and helpers to streamline automation.

Major Limitations:

• Not Dedicated to Visual Testing: Lacks specialized visual diffing and stabilization.
• Manual Baseline Management: Teams must handle baseline setup and updates.
• No Intelligent Comparison: Pixel-only comparisons cause noisy results.
• Minimal Visual Workflow Support: No dashboard or review processes.

Pricing: SeleniumBase is free and open-source with no licensing costs.

How Visual Testing Integrates With Selenium

Visual testing integrates with Selenium by extending traditional browser automation to include UI appearance validation. While Selenium handles user interactions and functional flows, visual testing tools capture screenshots at key stages and compare them against approved baselines to detect unintended visual changes.

Here is a step-by-step analysis on integrating visual regression testing tools with Selenium:

Step 1: Pick a Tool

The first step in adding visual testing to Selenium is deciding how visuals will be captured, compared, and reviewed. Selenium itself can take screenshots, but it does not compare them intelligently or manage visual baselines. This means teams must choose between lightweight libraries (like AShot or Needle) or dedicated visual testing platforms such as Percy.

For example, a team testing a marketing site with frequent UI changes may struggle with pixel-based libraries because animations, fonts, or ads introduce noise. In contrast, teams testing a stable internal dashboard might be comfortable starting with open-source visual regression testing tools that compare static screenshots.

Step 2: Capture Baselines

A visual baseline is the approved reference image that future test runs are compared against. In Selenium-based visual testing, baselines are typically captured during an initial test run when the UI is considered ‘correct’. This first capture is critical, as every future comparison depends on it.

For example, a Selenium test may navigate to a login page, wait for elements to load, and then capture a screenshot once the UI reaches a stable state. That screenshot becomes the baseline. If the login button later shifts position or a font changes unexpectedly, the next test run will detect it by comparing against this baseline.

Step 3: Run Tests and Compare

Once baselines exist, Selenium tests can be executed normally as part of local runs or CI pipelines. During execution, Selenium drives the browser while the visual testing layer captures screenshots at predefined checkpoints. These screenshots are then compared against the stored baselines.

For example, during a pull request build, Selenium might run regression tests across Chrome and Firefox. At each checkpoint, such as homepage load or form submission, the visual tool compares the new snapshot to the baseline. Any differences are flagged immediately, even if the test logic itself passes.

This is where visual testing adds value beyond functional assertions. Selenium might confirm that a button is clickable, but visual comparison tests reveal if it is overlapping another element, missing padding, or rendered incorrectly in a specific browser.

Step 4: Review Differences

When differences are detected, they must be reviewed to determine whether the change is intentional or a defect. With basic Selenium setups, this often means digging through image files or CI artifacts. Dedicated tools including free visual testing tools provide side-by-side comparisons that highlight exactly what changed and where.

For example, a reviewer can instantly see that a navigation bar height increased by a few pixels on Safari, or that a banner image failed to load on Firefox. These visual diffs make it much easier for QA, developers, and designers to speak the same language during reviews.

Effective review workflows reduce friction. Instead of debating whether a test failure is real, teams can visually confirm changes and decide whether to approve them or fix the underlying issue before release.

Step 5: Update Baselines

Baseline updates should be deliberate and reviewed, not automatic. Treating baselines as versioned assets helps teams maintain trust in visual test results and prevents real regressions from being silently accepted.

For instance, after approving a new color scheme, teams update the baseline so subsequent runs no longer flag those changes. Good tools allow baseline updates to be tied to branches or pull requests, preventing conflicts between parallel development efforts.

How Does Percy SDK Integrate With Selenium?

Integrating visual testing with Selenium becomes far more effective when combined with a purpose-built platform like Percy. Instead of treating visual checks as a separate process, Percy works alongside existing Selenium test suites to automatically capture and compare UI snapshots during test execution.

Percy’s Selenium integration is designed to support multiple testing scenarios and maturity levels. Teams can start small by adding visual checks to a few critical flows, then gradually expand coverage as confidence grows.

Because Percy integrates directly into CI pipelines and cloud execution environments, visual feedback arrives early, often before changes reach production.

Some things can’t be easily tested with unit tests and integration tests, and we didn’t want to maintain a visual regression testing solution ourselves. Percy has given us more confidence when making sweeping changes across UI components and helps us avoid those changes when they are not meant to happen.

Joscha Feth

Engineer, Canva

Common scenarios where Selenium + Percy integration works best:

• Extending existing functional tests with visual validation: Add visual checks to Selenium tests without rewriting test logic or creating separate visual scripts.
• Running visual tests alongside BrowserStack Automate: Execute Selenium tests on real browsers and devices while Percy captures stable visual snapshots.
• Kickstarting automated visual testing: Begin visual regression testing with minimal setup, even if visual automation is new to the team.
• Validating UI changes across frameworks and environments: Works with web applications, component libraries, end-to-end workflows, and static sites.
• Supporting custom integration needs: Percy SDKs and APIs allow teams to build tailored integrations when standard workflows aren’t enough.

This flexible integration approach allows teams to maintain visual quality, reduce regression risk, and scale automated visual testing without adding operational complexity.

Conclusion

Automated visual testing has become a critical layer of quality assurance as modern applications grow more UI-heavy and release cycles continue to accelerate. While Selenium remains the backbone of functional browser automation, it was never designed to manage visual change at scale. Relying on Selenium alone often leads to brittle screenshot comparisons, noisy failures, and manual baseline maintenance that slows teams down.

This is where dedicated visual testing tools fill the gap. By layering visual validation on top of Selenium workflows, teams gain confidence that UI changes are intentional, consistent, and user-ready across browsers and devices. Tools purpose-built for visual testing bring stability, smarter comparison logic, and collaborative review workflows that traditional automation frameworks lack.

For teams serious about maintaining visual quality without increasing maintenance overhead, pairing Selenium with a specialized platform like Percy offers a practical path forward. It allows teams to catch visual regressions early, scale coverage effortlessly, and keep UI quality aligned with fast-moving development, all without compromising existing automation investments.