As AWS and Google have started offering the advanced AI and ML platforms, it has gotten quite easier for the mobile app developers to integrate ML and AI in their mobile and leverage the benefits of this modern technology.
One such use of data science is imitating human tasks. Vision and speech are two crucial human interaction elements that data science has already started imitating. In this post, we'll be focusing on the 'vision' factor of AI. We live in a world where everyone has advanced and sophisticated smartphones with high-quality cameras and pixels.
The Artificial Intelligence tools available on the cloud-based platforms have proven super useful in the clicking, editing, storing, sharing, and filtering of the images and videos. Today, the masters in data science know how this technology is helping users in image recognition. Before we discuss the uses of data science in image recognition, let's have a look at the meaning of this concept.
What is Image Recognition?
Image recognition is one of the leading markets with total revenue being expected to reach approximately $39 billion by 2021. Image recognition is an element of the image processing procedure. The simplest definition of image recognition is the identification of the people, places, logos, objects, patterns, colors, and shapes, everything that can be located from the image. Data science is used in many fields, especially eCommerce, for image recognition.
The job of the user is limited to capturing the picture in their cameras and uploading the same. That’s it! AI tools start reading the image and extract valuable information from it.
• Face Recognition
The data science tools start recognizing the human face as soon as you open the camera. It also matches the face with all the pictures in its database. Basically, the facial recognition system of the AI reads all the features of your face and compares these parts with its database to locate a match. The facial recognition system is mainly used in unlocking a smartphone using your face. Other than that, it can be used for identifying the faces on social media posts and tagging people accordingly. However, it leads to privacy violations since AI reveals the user's identity without permission.
Furthermore, there’s no certainty that the facial recognition system will not match a random user’s face with that of a criminal. The technology does not offer 100% accuracy. However, the developers are improving the technology.
• Detecting Objects
AI has become so powerful that it not only helps the user in face recognition but identifies all the objects present in the camera. The tools scan all the objects and try to name and detect them. So far, visual search is one of the most developed and advanced tools of data science.
• Text Detection
If there is a text document, AI tries to read the text and identify what the image contains. It extracts written words from the image to identify what the picture is about.
• Pattern Recognition
As the name implies, data science identifies any special patterns in the image and matches it with its database. These patterns can either indicate a facial expression or a texture. Furthermore, the technology detects the color and shapes present in the image and provides the users with a proper insight into the contents of the picture.
• Logos and Landmark Detection
The AI tools try to fetch the artificial or natural landmarks and business logos in the image.
To know how this technology works and stores the faces in its database, you can watch machine learning tutorials online and get familiar with the image processing and recognition power of data science.