Role of Artificial Intelligence in Image Recognition

AI image recognition is another widespread trend gathering momentum these days — by 2021, its market is anticipated to achieve nearly $39 billion. The same report says that the image recognition market size is expected to grow at a CAGR of 19.5% from 2016 to 2021. Now it’s time to join the trend and learn what AI image recognition is and the way it works.

Image Recognition: What is it and how it works?

Image recognition has its application in eCommerce (for searching a product), gaming (to offer real-time gaming experience), automotive (self-drive vehicles), and various other industries.

Image recognition makes the software recognize various elements in an image, such as places, objects, actions, people, etc. Image processing converts a picture into digital form to perform various operations to fetch information from it. Image classification is another name for this technique. Facial recognition, visual search, creating a city guide, and content moderation are some of the applications of image recognition.

How AI is used for Image Recognition?

AI plays a vital role in image recognition. Here is how the technology assists image recognition to serve a variety of purposes.

Facial Recognition 

AI advances image recognition to recognize facial attributes from an image. The mapped features are then linked with the database stored to find a match. Facial recognition is primarily used for unlocking devices such as laptops smartphones, tablets, and more.

Besides, it is also used by social networking businesses to recommend the names of people in the photo we upload. We all have seen Facebook suggesting us to tag our friends when we upload an image on this social media platform. It recognizes facial features and then searches to find and recommend a suitable match.

Image Analysis

Artificial intelligence can provide effective details about a picture. It can make the image recognition to provide a synopsis of an image by analyzing the shape, color, and objects included in it. This feature can help to save a lot of time and effort.

Text Detection

With the help of artificial intelligence, image recognition can detect text from a picture and offer useful insights. We just need to upload a document or an image, and AI will read out the all texts from it. It means you do not have to spend hours doing it manually.

Pattern Recognition

AI image recognition can also help in recognizing particular patterns from an image. These patterns might comprise completely different textures or facial expressions.

Tools

Fortunately, you don’t need to develop everything from scratch — we can use already existing platforms and frameworks. Cloud Vision API from Google and Amazon Rekognition.

Google Vision

It is part of the Google Cloud platform and it offers a bunch of features that would most of the functions that we mentioned above. Google Vision provides API’s (called Cloud Vision API) for the respective features. As per official documentation:

“Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy-to-use REST API. It quickly classifies images into thousands of categories (such as, “sailboat”), detects individual objects and faces within images, and reads printed words contained within images. You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis.”

Features/Capabilities

Image labeling — The API assists in labeling a given image on the basis of different detectors or tags it can assign to that image by identifying the information it detects. The label range is vast — animals, vehicles, places, colors, food, etc.

Face, logo, and landmark detection —Identifying human faces (and animals), brand logos, monuments, and famous places. It is also capable of identifying multiple faces present in a picture and also identifies the person if it is a popular personality. It also gives the precise facial attributes and emotional states.

Optical Character Recognition (OCR) aka text detection — when you upload an image or document, it will read out all the contents in the form of texts even if the texts are scarcely present or the document is full of texts.

Detection of explicit content — this is a great feature using which we can detect the adult content from the user-generated image data. It gives the possibility of the presence of explicit or violent content.

Google search — using Google search data and algorithms, it tries to establish a relationship between the uploaded pictures and pictures available on the web. Using this it can search for similar images available on the web.

Amazon Rekognition

Amazon Rekognition platform is offered by Amazon as a service in AWS. The pictures and video content hosted on the S3 bucket can be fed into Rekognition for the analysis. It offers a lot of abilities similar to Google Vision like text extraction, object detection, and detection of explicit content, but there are a few impressive additions also.

There are two unique features to AWS Rekognition — Person tracking and Real-time video analysis. Person tracking allows you to detect and track the displacement of a person and take a wise decision based on it. Real-time video analysis can take instant decisions based on objects or activities identified in live video.

Amazon Rekognition is based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision experts to analyze tons of images and videos frequently, and it does not need the machine learning expertise to use.

Final Thoughts

In the machine learning field, image recognition is when the software detects elements of an image. In other words, it is the process of recognizing places, objects, actions, and more from an image. By integrating artificial intelligence in image learning, one can improve the capabilities of the software and make it offer great accuracy in the outcome. Here, in this article, we have highlighted image recognition, how it works, how AI can help to improvise image recognition and other allied information.

Our Strengths on AI

TechAffinity’s team can provide you with the best strategies and assistance for developing applications with Amazon Rekognition and Google Vision Cloud. Our engineers are truly proficient in integrating respective APIs, which in return helps us in delivering an application with powerful visual search and image analysis. Amazon Rekognition is one of the proven, scalable services which empower you to enhance your app’s user experience by adding image classification to it.

Vision Cloud and Amazon Rekognition have a lot of features to augment your application development.

• Seamless Integration into mobile and web apps
• Artificial Intelligence with improved facial analysis
• High Scalability to analyze billions of images per day

Get in touch with us by emailing your queries to media@techaffinity.com and know more about how to integrate Amazon Rekognition and Google Vision Cloud within your application and leverage its benefits. Our experts will be happy to help you.