When we talk about the vision of human or any living being, it all started billions of years ago. Fast forward to today, there is a plenty of life on the planet earth which all have very similar vision systems. This vision system builds with three components. One is eyes for capturing light and another is receptors in the brain for accessing it, and the third one is a visual cortex for processing it.
This vision system is all about engineered and balanced pieces of a system which help us understand things. In the past years, we've made even more progress to extend this amazing ability, not just to ourselves, but to machines as well.
We have much more advanced versions of systems and technologies that can capture photos right into digital form, now. This way, we've been able to closely mimic how the human eye can capture light & colors. But it's turning out that is just the part of easy. Understanding what's in the photo is lot more difficult. Consider this picture -
My human brain can look at it and immediately know that it's a deer. Our brains are taking help of some evolutionary context to help understand immediately what this is. But a computer doesn't have that same advantage.
To an algorithm, the image looks something like this -
Just long lines of binary values represent intensities across the object spectrum. As you are seeing, there's no context here, it is just a massive pile of data. It turns out that the context is the core of getting algorithms to understand image content in the same way that the human brain does. And to make this work for machines, we use an algorithm very similar to this using machine learning.
Machine learning allows us to effectively train the context for a data set so that an algorithm can understand what all those numbers in a specific organization represent. Advancements in machine learning and highly efficient data services are powering the growth of this technology. Businesses in different industries such as e-commerce, healthcare, automotive, etc are rapidly adopting image recognition.
Tools or devices like smartphones and scanners can play a crucial role in the growth of technologies like image recognition. From past few year we are the witness of constant increment in need for security applications, surveillance cameras and face recognition systems. But this is not just about identifying objects. You can identify places, people, objects, logos, etc in images.
Image recognition is a part of computer vision. Computer vision is gives ability to 'see', process, and predict images to computers. Many companies have adopted computer vision use-cases that are transforming the way their business run. Computer vision also includes event detection, object detection and recognition, image reconstruction, video tracking, etc.
How to use Image Recognition in your business?
Computer vision has been adopted by many businesses quickly. And the demand for it keep growing. Major businesses are using it for face recognition, object recognition, security, industrial automation, medical assistance and more vary by business industry and use cases. Let’s see how businesses are using image recognition to transform their services -
Searching and advertising is one of the mostly used use case of image recognition in E-commerce industry. Image recognition powered by deep learning can provide us advance capabilities like personalized searches, customer analytics, social media and conversation commerce, etc. With the date they got from image recognition, businesses can find insights for campaigns and marketing strategies. It is also capable to find user’s sentiments and expressions. This data will help marketers getting more return on their investments.
2. Social Media
Social media is also getting enormous benefits from image recognition. Facebook is one of the best examples of it. Facebook’s image recognition can recognize your family members and friends, identify their names and will give you suggestion to tag them while you upload picture with them. Many other social media platforms like LinkedIn & Twitter also use image recognition and object recognition features. Image recognition in social media make searches easy and effective.
3. Surveillance and Security
In surveillance and security industry, image recognition has many applications. Many big companies and security department use facial recognition to ensure security and identify crime. This process includes scanning of almost million images and adding them into deep neural networks. Then the system analyzes the images and compare them to suspects. In many cases it has proven to be very successful & effective and helped solving crimes.
4. Medical Analysis
In the world of computer and advanced technologies such as AI, machine learning, and deep learning; medical sectors are using image recognition to improve image analysis for medical analysis. It involves analyzing body parts, identifying diseases, and predicting possibilities of health problems. It is highly accurate, sometimes more than a medical profession to achieve perfect results.
Other than these industries, there are many sectors which are taking leverages of Image recognition and computer vision. Image recognition has several powerful applications that create a great deal. What do you think about this technology and what are the use case which you would like to cover with image recognition? Tell us your viewpoint and let us help you out with your requirements. From identifying requirements to delivering best machine learning model, Kevit can bring you all the benefits that come with these technologies within your business.
Here is one amazing example of Machine Learning and Image recognition -