Technology three to four decades before would have sounded like a novel on scientific fiction where robots would have played the mysterious man and computers would have been a deeply hidden treasure box. But the times have changed and the prophecy in those books has now become the reality of human existence. Machine Learning has become the protagonist of the tech world and is supporting Image Processing as a dear one. Machine Learning and Neural Network Algorithms are supporting Image recognition and have already taken it to the next level.
The Visual Revolution of this decade has been possible because of the advancement in Image Recognition due to the immense development of machine learning and deep learning. The visual effects we could only imagine in our wildest dreams are aesthetically turning into reality. Visual elements of an image are used to train the machines/computers and the machine learning algorithms are implemented to get the desired results for the future.
Image Recognition has become a part of our daily lives and knowingly or unknowingly we are using it more often than we think. Let’s find out how!
Top real-world applications of Image Recognition
Enhancing Security
Privacy and Security have always been a top-notch concern for everyone. Starting from home, business, industries to phones, laptops or any other form of gadgets; users want to make everything secure. Better image recognition along with deep learning algorithms are rendering real-time surveillance services to its customers. Visual security systems like CCTV cameras are running on a combination of image recognition, deep learning and IoT services. This technology has now jumped into our phones as well. For example, companies like Apple & Samsung are providing face lock security service in their phone and tablet’s security applications.
Social Media Filters
Stats have proven that not only teenagers but people of every age are using social media platforms these days. Instagram alone has 116million users in the U.S, 73million users in India and 72million users in Brazil. Whereas Snapchat has as of June 2019 had an overall 210million active users across the globe. The point that can be emphasised over here is that both of these social media platforms are highly recognised for their facial filters. And, these face filters are driven using image recognition techniques where the camera sensors help to detect the face points and accordingly adjust those entertaining filters. Not only the face, but the shades of the image itself can be customized as per your choice from the given bucket of available shade filters. Furthermore, Facebook is able to recognise the place, person or the object before the user could tag or label them.
Gaming
Image recognition with the help of 3D cameras has changed the gaming industry upside down. Xbox, Playstation by leveraging image recognition technology has allowed its gamer to incorporate the current time and location in the battlefield. Further, the gaming industry has very well embraced facial recognition technology. In fact, Forbes has reported that Chinese tech company Tencent will use facial recognition technology to identify and monitor its gaming players. This technology will be launched in the game ‘Honour of Kings’.
Visual Data Management & Visual Search Engine
Image recognition now is helping in managing visual data. Many websites like Unsplash, Pixel, Shutterstock, Pinterest and more are leveraging this technology. Further, this new search engine technology which allows visual search has made dynamic changes in the digital world. Visual Search Engines use image recognition techniques to identify and label objects, persons, places or animals in the images. Visual Search API allows the company the ability to do image-based searches in its software and come up with the most accurate result. Picsearch is the oldest platform and Google & Bing are the biggest platforms using this technology. Recently, the fashion brand Marks & Spencers launched a visual search style finder in their retail stores.
Automobile Industry
Self-driving cars have come a long way beginning from being partially controlled to being given complete control over it. This has been happening due to multiple reasons like the negligible chance of accidents, perfect traffic analysis, following traffic rules and regulation and lastly the navigation system. Not only the big old car manufacturers are engaged in this project but the tech giants are showing their interest in it as well. This industry renders services from various technologies and one of the most prominent is image processing and recognition. Image recognition helps to monitor road conditions, navigate and identify any obstacle during the journey. It becomes pertinent to utilise this technology to avoid accidents and follow traffic rules.
Healthcare Industry
Lastly, the healthcare industry too is leveraging image recognition technology. As the awareness to stay and maintain good health is increasing, medical staff and healthcare industrialists are opting devices that can monitor the concerned patient’s health regularly. The use of healthcare equipment has also increased with the advancement in machine learning and artificial intelligence. And the fusion between image recognition and artificial intelligence have come up with tools that allow us to monitor the patient’s health and detect emotions in real-time. Further, medical diagnosis demands to utilise the image recognition and processing techniques to give exact results.
