First of all, what is image recognition?

While the definition might seem self-explanatory, it’s helpful to think of image recognition in a specific way, particularly in the context of A.I. (Artificial Intelligence). We can do this by examining the workings of the human eye and how it processes an image. In simple terms, the eye takes the image as a set of signals which are then processed by the brain’s visual cortex, resulting in a vivid experience in a person’s memory. Image recognition essentially tries to emulate this process.

So what is the purpose of image recognition? Why does it exist? Well, the main reason for its existence is to assist in detecting images and videos at scale and in large volumes for various purposes. The main reason being that the human eye can only detect a certain amount of images in a given timeframe and in order to do it efficiently and at scale, Artificial Intelligence (in the form of image recognition) is needed.

What examples of image recognition exist today?

Facial, object, scene, and logo recognition are just a few examples of the different types of image recognition out there. Many companies, businesses, and brands in multiple sectors are using image recognition to help with tasks too vast for humans alone to complete. Industries such as e-commerce, automotive, healthcare, sports, social media, and gaming are now using some form of image recognition technology. Depending on the use case and the quality of the technology adopted, the need for human involvement varies.

Here at LogoGrab, we specialize in logo recognition for the following verticals: Social Media Monitoring, Brand Protection and Counterfeit Detection, Sports Sponsorship Monitoring, and Data Monetization. Our technology is fully automated and built for scale, meaning no manual or human input is required.

The industries mentioned above currently benefit from this type of image recognition, but what could future applications use this technology for?


Where will image recognition be seen next?

1. City guides:

Jetpac is a company that is at the forefront of image recognition used in city guides. Prior to this venture, Jetpac’s earlier product relied predominantly on Facebook photos. This focused on image processing capabilities that automatically detected the place in which the photos were taken, without the need for geotagging. These photos allowed the company to provide people with a curation of the top 10% travel destinations based on quality.

Jetpac now has a new product that is Instagram-based. Their city guides also use image analysis algorithms to extract data from Instagram that is publicly available. They then analyze the images’ locations to provide users with that information.


2. Self-driving vehicles:

Another future use for image recognition is the self-driving car. Some vehicles already have this functionality, but in the future, all cars are expected to detect obstacles and give the driver warnings about proximity to them.

In addition, autonomous vehicles of the future could guide drivers or users to specific destinations using image recognition. For example, the user can supply an image of a product to find the nearest store that sells something that looks like whatever is in the image.

3. Medical imaging:

Another area in which image recognition will be seen in the future is medicine. IBM researchers found that medical images are estimated to account for at least 90% of all medical data, which is the largest data source in the healthcare industry. According to John Smith, Senior Manager for intelligent information systems at IBM Research, detecting melanoma is one of the most promising near-term applications of automated image processing.

In the future, it’s expected that billions of images will be trained in order to help doctors and medical professionals in diagnosis. This is an exciting use case for image recognition technology as, if well-trained, the accuracy of this process will only increase over time.


4. Ad targeting:

As well as all of these use cases, image recognition will also be seen in advertising. It’s no secret that Facebook’s A.I. Research team (FAIR) has already developed facial and object recognition for the platform. However, this technology also has the potential to provide brands with vital information about their customers, such as their interests and demographics. Using image recognition, brands can determine which products appear most often in their customers’ photos.

This, in turn, will assist with a brand’s advertising efforts as they can target their audience with even more accuracy and further segmentation. In doing so, individualized ad placement, according to preference will appear for each user.

These are just some applications of image recognition technology expected to be around in the future. If you want to learn more about logo recognition and LogoGrab’s technology click here.