What is Reverse Image Search?

Reverse image search refers to a search technique where instead of text, you use an image to conduct a search. Most modern browsers and search engines support this feature.

The results of a reverse image search are typically other images, but the websites where those images were found are given below.

Reverse image search has a lot of uses, but one also wonders how it works. What is going on behind the scenes, and what are some real-world use cases of this technique?

In this article, we aim to answer all of those questions.

How Does Reverse Image Search Work?

Let’s begin by explaining how reverse image search works. The short answer is that several technologies enable its function. They are all listed below, along with explanations of what they do.

Computer Vision

First, we have computer vision. Computer vision is the technology that enables computers to “look” at pictures and videos just like humans would.

With computer vision, it is possible to extract data and information from images and videos. With the advent of AI and image processing, computer vision has become far more potent and useful.

Due to the advancements, computer vision is viable for reverse image search because it can gather information to look for quickly.

Image Processing

Image processing is a huge part of computer vision and, consequently, for reverse image search.

Image processing includes things like image resizing, image normalization, and filtering.

Let’s take a closer look at them and see what they entail.

In image resizing, the dimensions of an image are adjusted to make comparison between similar images easier. This includes changing the height and the width of the image.

Image normalization entails adjusting the range of pixel intensity values. Pixel intensity values are brightness and contrast. By bringing all pixel intensity values closer in line with “normal” values, reverse image search finds matches between different images more easily.

Finally, we have filtering. Filtering refers to multiple processes. It can include reducing noise, extracting really specific features, or simply enhance the edges of objects in an image. Filtration helps find similarities in images by focusing on specific parts or properties of an image.

These processes are necessary because they enable computers to understand an image.

Feature Extraction

Feature extraction is a part of image processing. In feature extractions, edges, textures, colors, shapes, and patterns are recognized. This is required to understand the image and do a reverse search of it.

In modern reverse image search tools, you can even specify if you want to search for specific features only. For example, if you are a botanist and are trying to identify a plant, you can draw a boundary around it and focus the search on that.

Machine learning plays a big part in extracting features. Deep learning models are trained to recognize similar features in thousands of images. These technologies enhance the accuracy of reverse image search.

Image Indexing

Reverse image search requires image indexing. All trained images and their features are stored in a database so that they can be consulted for reverse search.

The database does not just store images, it also breaks down their features such as:

Objects present in the image
Brightness and contrast
Color schemes

And all other miscellaneous features such as number of edges and shapes. This breakdown makes the reverse image search much faster and far easier.

The biggest search engines have huge libraries of indexed images. Their libraries consist of links to webpages that have the indexed image. The links are shown to the end user along with the images.

Similarity Measurement

Similarity measurement is the actual task where the current image and its features are compared to those in the database. The features extracted with deep learning are used to compare the current image with those in the database/index. The results are then shown to the user.

This is a simple, high-level explanation of reverse image search and how it works. Images are fed to the engine, their features extracted, and other images with similar features are found and shown to the user.

How to Do Reverse Image Search Yourself

Nowadays, you don’t need to be a programming expert or even have any knowledge of computer vision to do a reverse image search. Anybody with a computer and an internet connection can do a reverse image search easily.

Let’s look at some ways in which you can do it yourself.

With Google

Google provides you multiple options for conducting a reverse image search.

You can do it in two ways:

You use the image search option provided on the Google.com website.
If you are using Chrome, you can right-click on any image on a webpage and choose the “Search with Google” option.

The results of both methods are the same, you get taken to a results page where you can see other images similar to your own as well as the websites they were found on.

With Online Tools

Another method of doing a reverse image search is to use an online tool. There are plenty of free online tools that you can use and they all work in a similar manner.

So, here’s how you can use them.

Go online and simply search the term reverse image search
Most of the search results will be tools. Select one that catches your eye.
In the tool, copy-paste or upload the image you want to search and hit the search key.

The tool will prompt you with a choice. You need to select a search engine whose database you want to use. You can choose from Bing, Google, Yandex, and others. Whichever engine you choose, the results will be shown in a new tab.

Common Applications of Reverse Image Search

Now, let’s take a look at some real use cases of reverse image search.

Identifying The Source of an Image

The first and most obvious use is to find the source of an image. When you have an image or a screenshot and want to know where it’s from, you use reverse image search.

So, if you are writing something and find a good image to put in your write-up but don’t know the source of the image, you can use reverse image search.

You can also use reverse image search to find the original media from which some memes were taken. Reverse image search is also often employed in the quest for lost media.

Sometimes, you have an image, but you want something similar yet different. A simple way would be to go online to a picture website and use some tags to narrow your search to find a suitable image.

Or, you could do a reverse image search on the original image and find similar images that way. All you have to do is copy your image and paste it into the search bar of a search engine. In a matter of seconds, you will get a variety of exact copies and similar images. Then, just take your pick from the lot.

Finding Information About an Object in the Image

Another use of reverse image search is finding information about a particular object in an image. For example, plant enthusiasts can take a picture of a plant and use reverse image search to find more information about the plant.

Here’s another scenario. Imagine you found an outfit in someone’s picture. You like the outfit but don’t know where it’s from or what brand it belongs to. You can do a reverse image search on the picture and draw a boundary around the outfit.

This prompts the search engine to find only images and sources related to the outfit. This way, you can find the shop where you can buy the outfit yourself.

To Determine Authenticity of Online Profiles

In the modern internet, it is extremely easy to create fake online personas. Fake profile pictures, fake names, and fake addresses are all quite easy to come by.

Some people who have nothing better to do create fake profiles on websites and simply troll others. Usually, you can identify a troll by checking their activity that they have made public, i.e., the kind of posts and comments they have made.

But most social media apps allow you to make your profile private and hide it from view. So, it makes it harder to find fakers. However, with reverse image search, you can do it somewhat reliably.

By using reverse image search on their profile and banner pictures, you can identify whether the images used were just lifted from some random source on the internet or not.

If they are real, then you won’t find a good match and the results will be few as well. If they are fake, you will probably find a bunch of websites that provide similar images.

In this way, you can determine whether the online persona is a troll or not and block them.

Conclusion

This concludes our discussion on reverse image search. We briefly covered how reverse image search works, what are the technologies involved, and its real-life uses.

Reverse image search is incredibly accessible today. You can use free online tools for it, and many search engines like Bing and Google can do it for free as well. So, go out there and experiment with it without worry.