What Is Visual Search? Definition, Examples

Ever since the world transitioned into a digital space, it has become more open to evolution. You may have noticed that trends nowadays don’t last very long. One moment, they’re at their peak, and just a few days later, they fade away. Such a quick turnover is all because of technological advancement.

The advancement in technology has also impacted the way we search for information. Previously, we relied entirely on typing words into a search bar to find something. But nowadays, people also use visuals to navigate the web more intuitively. But what exactly is this new visual search method? If you’re eager to find out, this blog post is just what you need.

Here, we’ll discuss everything about visual search, from its definition and meaning to its working mechanisms and examples. So, let’s jump right into this blog post. Shall we?

Introduction to Visual Search — Meaning and Definition

To better understand the concept of visual search, let’s break down this terminology into its individual components. As you can see, visual search is a combination of two words: visual and search. The word ‘visual’ refers to ‘something seen,’ like a picture or image, whereas ‘search’ means ‘to find something.’ So, if we combine the meanings of both these terms, the ‘visual search’ terminology gives the meaning of ‘using a picture to find something.’

Now that you’ve understood the meaning of the visual search, you’ll be better able to comprehend its definition. So, in light of the above-extracted meaning, here is a refined definition of visual search:

Visual search is a technique for finding relevant results using the query’s visual characteristics, such as color, shape, and pattern.

Hence, people also use the term ‘image search’ to refer to the visual search methodology.

A Brief Overview of Visual Search Working Mechanism

The text-based search approach matches the terms in the search query to the description, keywords, and metadata. Similarly, the image search method generates results by matching the visual characteristics of the query. However, what differentiates these two methodologies is the technology used to find the relevant results.

For instance, text-based searches use Natural Language Processing (NLP) to understand whether a particular result matches the intent and keywords of the search query. On the other hand, the visual search method relies on the combination of the following cutting-edge technologies:

• Deep learning.
• Image recognition.
• Machine learning.

These three advanced technologies help the image search technique accurately compare colors, objects, patterns, or shapes and find relevant results.

Thus, when you upload a picture as a search query, the algorithms of most image search systems quickly employ picture recognition, machine learning, and deep learning (CNN) technologies to return the results. Those results generally include one or all of the following information:

• Product information.
• Relevant web pages.
• Similar images.

A Few Most Popular Examples of Visual Search

The visual search method may seem like a new technique, but it’s not. It has been around for quite some time. To be more precise, the world first saw the practical implementation of image search methodology back in the early 2000s. But it has improved a lot since then. So, in light of that enhancement, here are some of the most famous examples of visual search available nowadays:

Google Lens

Much like its (text-based) search engine, Google Lens is one of the most popular image search examples nowadays. Some recent studies show that Google Lens holds 70% of the market share these days. But what exactly is the reason for its popularity?

Google Lens uses artificial intelligence and machine learning to identify landmarks, objects (like animals, plants, or products), text, and other things. Due to its multipurpose nature, many smartphone developers these days are integrating the functionality of Google Lens directly into the gallery of the latest Android phones. This helps people discover similar products or translate pictures of foreign text in real-time.

Bing Image Search

According to research conducted recently, Microsoft’s Bing visual search feature is the world's second most-used image search engine, with a market share of 15%. Like Google Lens, Bing’s visual search allows people to find images and related content according to the visual characteristics of the uploaded picture. However, it doesn’t recognize text as well as Google Lens and doesn’t let you translate the recognized text.

Besides the common information, the Bing image search also provides context for each generated result. That context generally includes the following data:

• Related news articles.
• Website associated with the image.

Yandex Image Search

Yandex is a Russian search engine that primarily targets the Russian audience. Therefore, its visual search is less popular than Google Lens and Bing image search. However, studies suggest that Yandex still holds a 5% market share in terms of visual search.

This image search engine has strong image searching capabilities for recognizing the Russian context in pictures. But this doesn’t mean that it is useless for other languages. Regardless of your image’s language, Yandex works flawlessly to discover similar pictures online with the help of its reverse image search technology. So, you can filter your search results here with the help of the following factors:

• Color.
• Size.
• Picture type.

Additionally, Yandex uses image search to generate recommendations for relevant related searches.

SmallSEOTools

SmallSEOTools is not necessarily a search engine like Bing, Google, and Yandex. Rather, it is an online resource that provides reverse image search services using the database of all the popular search engines.

Like the three examples above, the visual search tool of SmallSEOTools uses advanced technologies, such as AI and CBIR, to generate relevant results according to the query. What’s great about this image search tool is that it provides the benefits of Google Lens, Yandex, and Bing under one hood. Therefore, if you want to explore the database of all three popular search engines simultaneously, you can get assistance from SmallSEOTools’ reverse image search utility.

eBay and Amazon Visual Search

Amazon and eBay are two giants in the e-commerce business. These platforms have integrated the visual search feature into their online stores to improve customer experience and generate more revenue. With such a feature, users can quickly locate similar products available for sale, be it an outfit or something else. But that’s not it.
In addition to finding relevant products, the image search feature on eBay and Amazon also provides comparisons, comprehensive product information, and reviews of similar items. This helps people make better purchases.

Summing Up — The Conclusion

To sum up, visual search is a type of search query that allows people to discover items or information based on visual content. It uses the visual characteristics of pictures to generate relevant results. This type of search has become increasingly popular in recent years as technology has advanced and computer vision and analysis capabilities have improved. However, we believe that even more incredible advancements in visual search are about to occur in the near future. If this happens, the image search will become an even more powerful tool for searching and discovering information based on visual content.