A revolutionary change in the world of technology was the development of image recognition.
Image recognition is a technique to identify the elements of an image. Various industries across the globe, including healthcare, content designing, e-commerce, automotive, etc., have adopted image recognition.Due to its increasing prominence, the global image recognition industry can grow to $53 billion by 2025.
This article will let you know more about image recognition and its extensive applications.
What Is Image Recognition?
Image recognition is the technology that can identify objects, people, logos, places, emotions, and other such variables in your images and videos.
Image recognition is based on machine learning and AI and is a part of computer vision. It is commonly used for detecting and tagging people, objects, and places when you have many video or photo databases.
Trends In Image Recognition
With newer trends in the image recognition market, there will be a paradigm shift in image recognition shortly.
Thousands of people share content on online platforms. Many of them also share illegal and inappropriate pictures and videos.
Social media platforms that have user-generated content face a lot of difficulty in efficiently monitoring and filtering the content uploaded by people. With billions of people posting every day, they find it difficult to block offensive content.
If we do not moderate content the right way, it can affect people and their reputation. It can also give rise to several legal and mental issues.
Content moderation filters such offensive content. It is done by both humans and AI to remove aggressive, pornographic, and illegal content. This helps protect users from bullies and offenders online.
A few AI machines can filter and block out offensive content posted every day by billions of people. It is less expensive than human moderation and is also easier to scale.
With the advancement in technology, image tagging will continue to grow when using image recognition. Image tagging is used to automatically assign tags or keywords to a huge database of pictures and videos.
The AI is trained to look at the pixel content, extract the features, and analyze and detect the images that suit the tag. It is one of the best time-saving solutions for companies that deal with huge amounts of visual content from different places.
It is mainly used in photo-sharing apps, like Google Photos or iCloud, by publishers, advertisers, and agencies who aim to work with contextual advertising.
Visual search is used to look for images based on a certain sample image. It lets you search and look at products that are similar to the image you provided it with.
For instance, you can feed in a picture of a product you clicked from your camera and use that to find similar products on the web. You do not have to provide extra text descriptions, which often do not accurately describe what you are looking for.
Retail stores for clothes and home décor have been using this technology to make the user experience easier and provide recommendations.
Facial recognition is another technology used for law enforcement and government identification. It is becoming more popular with the growing demand for contactless payments, biometric systems for security, etc.
It has the highest growth potential as it is becoming common in the security and non-security industries. Various police officers use apps to identify people and their faces while they are on the investigation.
5 Innovative Uses Of Image Recognition
1. Image Recognition in Automobile Industry
As image recognition technology advances, car manufactures across the globe are researching and developing self-driving cars. Various tech giants have been investing in the same.
The main goal behind such cars is the reduced rate of driving accidents, to keep a check on people, and maintain traffic rules.
2. Emotion Detection in Healthcare Industry
Image recognition technology has evolved the healthcare sector in more ways than one. This technology has been a blessing, especially for patients.
With machine learning and AI advancement, image recognition has a greater demand in the medical industry. Various microsurgical procedures are conducted by robots that depend on image recognition techniques and computer vision.
Image recognition is used in the real-time emotion detection of the patients’ emotions to understand what they go through.
3. Fusion of Virtual and Augmented Reality
Also known as merged reality, this use of image recognition overcame the problems in VR and AR. Merged reality makes sure that consumers get surreal virtual-world experiences that seem more natural and more dynamic.
For instance, Microsoft’s new Windows Holographic Shell is a wireless headset that lets you induce real-world objects into your imaginary world using 3D cameras.
4. Image Recognition in the Security Industry
Image recognition has become increasingly popular in the security industry, especially in malls, offices, and restaurants. Smartphones, online and offline banking, and office identification procedures all use image recognition in security systems.
Today, we have drones, cameras, and face-recognizing biometric systems, making it so easy to protect your identity and catch culprits in real life.
The most innovative use of image recognition in home security is home automation cameras with AI technology for baby and pet monitoring and location training.
5. Image Recognition in Social Media
Image recognition is used to find visuals on social media. You can use a picture to look up a location or a person on any social media page.
These image recognition tools can search thousands of sites rapidly and help discover the information you are looking for within milliseconds.
Companies like Facebook have also started using image recognition to develop features for visually impaired people. These features use automatic text with face recognition technology to produce accurate descriptions of pictures and videos.
Image recognition has changed how we look at the world and perceive our surroundings. It is a powerful tool that benefits several industries and is used mainly for validating data. The progress of machine learning and newer trends in technology can help boost the growth of the image recognition industry.