What Is Computer Vision? Everything You Wanted to Know
Computer vision is evolving rapidly and its advancement impacts many areas of our life. Algorithms can already detect cancer and control cars and airplanes and in some cases, computer vision even surpasses people in performing certain tasks. With that said, many companies are picking up the trend and start to offer custom solutions in the field of computer vision.But what exact benefits does this technology bring to industries? In this article, we explain what computer vision is, how it works, and how it can benefit your organization.
Computer vision: defined and explained
Computer vision is a scientific field that focuses on training computers to interpret and understand the visual world, just like humans do. In other words, computer vision is the recognition of patterns of a visual object.
Computer vision can perform a number of tasks: classification of objects and images, face recognition and image segmentation, and visual tracking. All of them are aimed at answering one question: what is shown in a picture? Despite the seeming triviality of the question, answering it is not really easy.
How does computer vision work?
In order to understand why computer vision delivers highly accurate results, let’s look at the way it works. Computer vision is a subset of Machine Learning which means it learns through massive data sets.
First, an ML model receives a certain number of pictures of an item that needs to be recognized. The model then runs the images through several levels of processing that make up a neural network to distinguish your chosen item from many others, step by step.
The first levels of learning and recognition are aimed at evaluating such basic features as lines or borders between light and dark parts of an image. Further, the model explores more complex details - shapes or edges. In this way, the model analyzes the data over and over again until it recognizes the differences and eventually recognizes the image.
Benefits of computer vision
The unique selling point of computer vision is that it can imitate human vision to quickly perform monotonous or complex visual tasks. While a human eye can only process a limited amount of information, computer vision efficiently analyzes both real and virtual worlds and collects huge amounts of data faster and more accurately. Here are other significant benefits of computer vision:
- High efficiency: a computer vision system can perform monotonous tasks at a high speed, surpassing human employees and the efficiency of the system is independent of external and human factors (i.e. lack of light).
- Consistency and accuracy: computer vision consistently delivers the same results and significantly reduces the possibility of an error. This, in turn, helps maintain high quality of services.
- Reduction of costs: due to the speed and accuracy of performance, the use of computer vision can help minimize the costs spent on image recognition.
To sum up, the use of computer vision brings automation, accuracy, and speed into your processes. Now let’s see how this technology is applied across industries by using real-life examples.
Transportation: recognition and classification of road objects
The growing needs of the transportation sector have spurred technological development in the industry, with computer vision at its center. The most well-known example is an autopilot car, like the ones Uber and Tesla have. These cars are equipped with cameras that shoot video from different angles to detect and classify various road objects (such as road signs or traffic lights). As well, these cars are capable of creating 3D maps and estimating traffic. ADAS (Advanced Driver Assistance Systems) technology researchers are combining various computer vision techniques to develop algorithms that will enable vehicles to take full control of the driving process.
But what’s the need in self-driving cars? The biggest benefit is a high level of autonomy that reduces risky and dangerous driving behavior. As well, smart cars can help reduce traffic congestion and lower the level of emissions.
Manufacturing: quality assurance
The manufacturing industry has already introduced a wide range of automation solutions based on computer vision:
- Detection of product defects;
- Precise product assembly process;
- Safety and security standards for employees;
- Barcode and text analysis.
Large-scale production sites often have difficulties with accurately detecting defects in manufactured products. This led to the introduction of computer vision into production. Pharma Packaging Systems equipment for the pharmaceutical industry is a case in point. The system is designed for automatic counting of tablets or capsules on production lines. Another example is WebSPECTOR - a surface inspection system that detects defects on products and collects metadata associated with an image to classify errors by their type and degree.
Retail: automated cash registers and cashless stores
The retail industry has also started to use computer vision solutions to meet customer needs more accurately and better manage the inventory. One of the most popular examples is Amazon Go - a chain of partially automated stores that use several technologies, including compter vision.
A high-tech shopping experience starts at a store entrance where customers need to authorize by using a QR code in an Amazon mobile app. After entering the store, shoppers have to scan the code and after that, they can proceed to the shopping. The app runs in the background and tracks the list of purchases while a video surveillance system tracks the customer's location. RFID tags on shelves determine whether an item was taken off the shelf and if a shopper changes their mind, they can put the item back - in this case, it will be removed from the shopping list. When a customer leaves the store, the app automatically performs the transaction.
This is not the only use case of computer vision in retail. This technology also allows to study customer behavior and monitor the number of shoppers in a certain aisle or area, which is a great advantage for marketers. But overall, given the convenience of cashless payment and improved shopping experience, the need for computer vision in retail will definitely grow.
Finance: Know Your Customer (KYC)
Financial institutions used to have a hard time breaking through with innovation. However, the industry has been slowly shifting towards digital transformation and computer vision, in particular, proved to solve certain long-standing challenges for financial organizations.
These challenges include cybersecurity, customer experience management, and transaction identification and authentication. One great example of using computer vision in finances is KYC which stands for Know Your Customer. A spanish bank BBVA uses facial recognition to confirm client identities when clients submit their photo IDs. During a video call, a client can open a personal account on their smartphone and successfully perform user authentication.
Traditional KYC processes typically require a lot of documentation and a lot of time. But with computer vision, the process can take a few minutes instead of an hour and this results not only in a much better user experience but also in higher accuracy.
Healthcare: disease detection
The healthcare industry was probably one of the earliest adopters of computer vision and today, the number of applications of this technology in the industry is quite impressive. One of the biggest examples is the use of computer vision and deep learning technologies for brain tumor detection. Since tumors tend to quickly spread to different parts of the brain and to the spinal cord if left untreated, their early detection is critical. As well, computer vision can efficiently recognize and detect any warning signs or indications of other diseases and hence, the use of this technology greatly elevates the healthcare services.
Technology has changed the face of the world, and computer vision plays a huge role in these changes. The examples listed above are just the tip of the iceberg and we can expect computer vision to continue being a driving force behind the transformation of industries.
Business leaders need to assess how computer vision can impact the growth of their organization. If you have a certain challenge that you've been trying to solve for a while, maybe now is the perfect time to take a look at the innovative AI software available on the market.
Wow. That was quick and precise analysis of machine and deep learning.