In our previous articles, we discussed the recent developments in Artificial Intelligence. Now, we will explore Computer Vision technology in its depth.
Computer Vision Technology is a field of Artificial Intelligence. The latter strives to emulate and provide a realistic simulation of human comprehension of the problem statement, which is natural, more accurate, and emotionally intelligent.
As the name suggests, Computer Vision is a technology that enables computers and machines to perceive (“see”) visual information- images and video like humans. The idea is to train the systems to analyze image pixel by pixel and provide realistic solutions.
The primary tasks of computer vision include object detection, face recognition, biometrics, and more. As you can see, these use cases are an inevitable part of ensuring secure processes in industries today. Computer Vision is transforming various industries today, retail and manufacturing being the prominent ones.
Through this article, we’ll try to explore this subject in depth, with its applications, challenges, and future scope.
What is Computer Vision?
“When the computer gets eyes.”
Computer Vision technology is a subfield of Artificial Intelligence that focuses on how computers can be made to comprehend and interpret visual information-image and videos.
It involves algorithms, machine learning, and computer science, empowering computers to extract visual data. It involves a wide range of tasks which includes:
- object detection,
- video analysis, and
- autonomous system.
What are the tasks performed by Computer Vision technology?
Some classic examples of Computer Vision tasks are
Image and Video Analysis
This includes the process of recognizing a visual (image or video) just the way it is. For example, there is a digital photo of a dog and a cat. With image and video analysis, the system can classify it the way it is (as perceived by humans). It extracts the data of objects, people, and activities through algorithms and patterns.
Object Detection and Recognition
This task aims to detect a specific object within an image/video. It helps in the identification of damages in the digital photo. Object detection helps in recognizing damage in the machinery, which requires maintenance. Another aspect is object tracking which helps in identifying the movement of a specific object.
Image Segmentation and Stitching
Computer vision system can be used to separate images into the foreground and background components. At the same time, it assists in stitching images or videos by combining multiple snaps into one video.
Besides, computer vision technology performs various other tasks, such as face recognition, image/video compression, optical character recognition, and more.
How does Computer Vision work?
Computer Vision recognizes patterns/characteristics of an image and analyzes each pixel with great precision to arrive at a collective result. This technology is a deep learning algorithm that incorporates distinctive neural networks known as Convolutional Neural Networks.
Let’s consider the analogy of how we teach kids to learn everything from scratch. We show them apples and oranges to tell them that a particular form (fruit) is called an apple/orange by showing them the fruits’ features, shape, and color. We try to familiarize them with the form (apple and orange) and its name.
The process of computer vision is similar. A computer is fed with imagery data pixel by pixel, divided into classes. Now, just as a kid won’t grasp this info in one go. So we repeatedly show them the visuals to familiarize them with that particular image. We also show them the variations (for example, green apple, rotten apple, and more) that may exist as they become comfortable with it.
Just like that, we feed the computer with such classifications. But a computer doesn’t understand words. It understands binary language in 1 or 0. So, we fed them data the same as associated with particular imagery.
In this way, a computer is taught a wide range of human expressions, names, images, and more. So, it perceives like a person.
There are a few aspects to making it happen. The technology is blended with the following to arrive at such an accurate conclusion:
- Signal Process
- Pattern Recognition
- Image Processing
- Artificial Intelligence
- Mathematics and more.
Advantages of Computer Vision Technology
Computer Vision can carry out repetitive tasks with great efficiency and accuracy. It offers an innovative edge to your services. Let’s explore some distinctive advantages of this technology.
- It dramatically reduces the need for human labor in quality control, security, and surveillance.
- The large quantity of data can be analyzed with great accuracy leading to increased efficiency and productivity.
- It ensures safety in various applications such as drones, industrial robots, and more.
- Through various features of computer vision technology, the user experience can be significantly improved. It can push relevant content to the user based on their behavior. It can also provide recommendations and customized services accordingly.
- Computer Vision Technology can significantly reduce costs by automating various processes which would otherwise use manual labor/workforce.
Applications of Computer Vision Technology
The top applications of this revolutionary technology in varying industries today are as follows:
Manufacturing and Retail
This technology can be used in the quality control and monitoring of product lines. It is also super helpful in identifying defective products (by employing image segmentation). Other aspects of computer vision enhancing this industry include storing traffic, tracking inventory, and analyzing customer behavior.
Computer Vision can greatly ease the diagnosis/detection process of any condition, such as cancer, heart disease, etc. CV Technology is playing a key role in enhancing healthcare services by promoting an efficient, more accurate, and cost-effective alternative. It’s helping professionals make better decisions. For example, Medical imaging helps in conducting visual analysis of a particular organ. Thus, it helps the medical professional detect possible problems like blood clots, tumors, etc.
One of the prominent applications of Computer vision is enhanced security. Image processing helps in recognizing any suspicious activity. It’s a great way of monitoring crowded places, streets, etc.
This task helps improve the efficiency and accuracy of tasks such as quality control and inspection.
There are countless use cases of computer vision technology today. Some of them are Agriculture and Robotics. This technology is truly revolutionizing the agro-industry. Through image detection, it can find defective crops. It also analyzes the soil quality. Another prominent use case included is robotics.
Computer Vision in Your Social Media App
Various social media applications are incorporating computer vision technology to provide an innovative interface to enhance the user experience of the subscribers.
For example, Snapchat is actively using face recognition to create interactive filters. We are sure most of you would have a fun time exploring Snapchat filters where your tongue sticks out the moment your face fits into the frame or the crown fits into your head. With facial detection technology backed with image processing techniques, the application derives a wide range of interactive filters.
Almost every prominent application utilizes computer vision technology to perform certain activities. For instance, have you noticed how Facebook suggests the name of the person you could tag in the photo posted in your profile? Yes, that’s none another than computer vision making the correct guesses. Google photos work on the same principle.
Instagram, Pinterest, LinkedIn, etc. incorporate this technology to make their interface super fast and innovative like never before.
Are there any challenges related to Computer Vision Technology?
Who imagined computers would have a vision akin to that of a human? However, that’s the living reality right now. It’s a highly intricate and sophisticated subject that is yet evolving. Emulating human vision is a complicated discipline (‘Even us humans don’t have it perfected yet.’).
The implementation of CV hardware is still a challenge. Developing a hardware and software setup to assist the functioning can still be a challenge. CV requires a high-definition camera backed with a supporting setup because it requires both algorithm computation and faster memory access.
Right now, there is relatively little expertise in computer vision. Sometimes, the lack of resources can also pose limitations in implementation. Besides, technology can still be quite costly to execute.
At the same time, it’s an undeniable fact that CV technology is the future. Positive developments are expected in the future and that will surely curb these challenges.
AI technology, in general, is thriving at an exponential rate. The more it’s becoming personalized, the more technologies like computer vision will flourish. The way this technology is transforming the healthcare industry, manufacturing industry, etc., it’s expected (source) that a global market share of USD 2,384.2 with a CAGR of 29.5% from 2021 to 2026 will exist.
These stats clearly indicate that computer vision is rebuilding the “vision” of the 21st century. It’s not a far-off reality either.
From your quirky socializing ways through Snapchat to transforming your “daydream” of the driverless car into reality, computer vision is elevating the human experience. CV systems are of prime importance in ensuring stringent security through surveillance.
So, through the computers’ eyes, the future looks dandy and bright.
Stay tuned to https://www.rapidinnovation.io/ for more technical dives!