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Image Recognition

Everything about Image Recognition


What is image recognition?

Image recognition is the ability of a computer powered camera to identify and detect objects or features in a digital image or video. It is a method for capturing, processing, examining, and sympathizing images. To identify and detect images, computers use machine vision technology that is powered by an artificial intelligence system. A typical image recognition algorithm includes the following:

  • Optical character recognition
  • Pattern matching and gradient matching
  • Face recognition
  • License plate matching
  • Scene identification


How does image recognition work?

Image recognition technology works by detecting salient regions, which are portions that contain the most information about the image or the object. It does this by isolating the most informative portions or features in a selected image and localizes them, while ignoring the rest of the features that may not be of much interest. The process uses an image recognition algorithm, also known as an image classifier, that takes an image as input and outputs what the image contains. For an algorithm to know what an image contains, it has to be trained to learn the differences between classes. For instance, if the goal of an image recognition system is to detect and identify dogs, the image recognition algorithm needs to be trained with thousands of images of dogs and thousands of images of backgrounds that do not contain any dogs.

How image recognition is used in business?

In the commercial world, the major applications of image recognition are face recognition, security and surveillance, visual geolocation, object recognition, gesture recognition, code recognition, industrial automation, image analysis in medical and driver assistance. These applications are revolutionizing the business world, across many industries, and here’s how:

In E-commerce
Image recognition has been highly adopted in e-commerce, including search and advertising. Today, mobile applications use the technology to identify specific products, providing potential customers with a more engaging experience of the world around them. It presents a more interactive view of the world by making everything searchable.

Business process management
Image recognition technology can assist in the identification process during business operations. An example of this would be the replacement of traditional ID cards with Face ID. In the workplace, this can be used to determine if a person is granted access to official work documents or simply to check in. Another example where image recognition is applicable for efficient business operations is in the manufacturing process. Machines equipped with image recognition can automatically detect defective products in the manufacturing pipeline.

Automotive industry
Self-driving cars are the buzz in the automotive industry and are already being tested in the U.S. and other parts of the world. These advancements in the automobile world are made possible by computer vision technology which uses AI image recognition. Computer vision systems powered by deep learning are trained using thousands of images such as road signs, pathways, moving objects, vehicles, and people and are fed into the systems neural networks. The systems get intelligent as more training data is fed into the system and this is how autonomous driving is enabled.

The Benefits of Image Recognition

Image recognition can really help you with digital marketing. By integrating the application’s programing interface to your text-based analytics platforms, you will be able to offer visual insights to your customers without the expensive product creation that uses logo detection. Image recognition can also help you monitor ROI and protect your brand. You will be able to track how a sponsorship is doing with image and logo detection and this will help you determine how much revenue you will get in return. Therefore, integrating an image recognition application programing interface is an easy way of giving your customers the best service.

When using image recognition, you can easily transposition digital information. As opposed to virtual reality, image recognition doesn’t replace your environment with a digital one, instead, it adds more perks to it. in addition, you can easily organize your visual memory. Image recognition software can help you make mental notes through visual. If you take an image, its computer vision will match up with the visual background information, meaning that you can get information about wine bottles, books, DVDs, and many more by simply taking a photo of their covers or labels. When you have these images in your computer, you can then search for the information they contain, counting on keywords, location etc.

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Technical Specifications

The table below shows how FaceMatch SDK performs on the Labelled Faces in the Wild (LFW) dataset:

FPRTPRThreshold (Inverse of distance)
0.10.99900 ±0.002130.55448
0.010.99667 ±0.005370.59791
0.0010.99367 ±0.006050.62989

FPR = False Positive Rate
TPR = True Positive Rate

These results are an indication only and are based on the specific dataset Labelled Faces in the Wild. Customers can expect similar performance, with possible variations due to hardware and the availability of annotated data.