{"id":39178,"date":"2022-06-09T19:37:44","date_gmt":"2022-06-10T02:37:44","guid":{"rendered":"https:\/\/app14743.cloudwayssites.com\/?p=39178"},"modified":"2026-01-09T15:15:10","modified_gmt":"2026-01-09T20:15:10","slug":"visual-ai-vs-pixel-matching-dom-based-comparisons","status":"publish","type":"post","link":"https:\/\/app14743.cloudwayssites.com\/blog\/visual-ai-vs-pixel-matching-dom-based-comparisons\/","title":{"rendered":"The Benefits of Visual AI over Pixel-Matching & DOM-Based Visual Testing Solutions"},"content":{"rendered":"\n

The visual aspect of a website or an app is the first thing that end users will encounter when using the application. For businesses to deliver the best possible user experience, having appealing and responsive websites is an absolutely necessity.<\/p>\n\n\n\n

More than ever, customers expect apps and sites to be intuitive, fast, and visually flawless. The number of screens across applications, websites, and devices is growing faster, with the cost of testing rising high. Managing visual quality effectively is now becoming a MUST.<\/strong><\/p>\n\n\n\n

Visual testing<\/a> is the automated process of comparing the visible output of an app or website against an expected baseline image.<\/p>\n\n\n\n

In its most basic form, visual testing, sometimes referred to as Visual UI testing, Visual diff testing or Snapshot testing, compares differences in a website page or device screen by looking at pixel variations. In other words, testing a web or native mobile application by looking at the fully rendered pages and screens as they appear before customers.<\/p>\n\n\n\n

The Different Approaches Of Visual Testing<\/h2>\n\n\n\n

While visual testing has been a popular solution for validating UIs, there have been many flaws in the traditional methods of getting it done. In the past, there have been two traditional methods of visual testing: DOM Diffs<\/strong> and Pixel Diffs<\/strong>. These methods have led to an enormous amount of false positives and lack of confidence from the teams that have adopted them.<\/p>\n\n\n\n

Applitools Eyes<\/a>, the only visual testing solution to use Visual AI, solves for all the shortcomings of visual testing – vastly improves test creation, execution, and maintenance.<\/p>\n\n\n\n

The Pixel-Matching Approach<\/h2>\n\n\n
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This refers to Pixel-by-pixel comparisons,<\/strong> in which the testing framework will flag literally any difference it sees between two images, regardless of whether the difference is visible to the human eye, or not.<\/p>\n\n\n\n

While such comparisons provide an entry-level into visual testing, it tends to be flaky and can lead to a lot of false positives, which is time-consuming.<\/p>\n\n\n\n

When working with the web, you must take into consideration that things tend to render slightly different between page loads and browser updates. If the browser renders the page off by 1 pixel due to a rendering change, your text cursor is showing, or an image renders differently, your release may be blocked due to these false positives<\/a>.<\/p>\n\n\n\n

Here are some examples of what this approach cannot handle:<\/p>\n\n\n

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Pixel-based comparisons exhibit the following deficiencies:<\/p>\n\n\n\n