Top Computer Vision Applications Across Industries in 2023
The basic concept behind computer vision (CV) is to enable machines to see and understand the visual world. While some entrepreneurs only start recognizing this sphere, the rest are already using all the benefits it gives.
The size of the global CV market was estimated at 9.45 billion USD in 2020 and is expected to reach 41.11 billion USD in 2030. The growth of 16% CAGR during ten years is no joke. So what is behind it?
Computer vision applications allow companies to process data faster and more efficiently, reduce operational costs, and improve existing products and services. You would probably say that it sounds too general, and you are right. We are here to introduce you to the niche and its promising trends.
What can computer vision do, and how will this technology develop in 2023? Let us find out step by step.
What Is Computer Vision? Basic Terms and Principles
Computer vision is an AI-based technology that derives meaningful insights from the visual world (images or videos) and generates recommendations or takes actions accordingly.
Computer vision projects are mostly based on image segmentation techniques. Image segmentation is the first action taken to understand the visual input and proceed to the next steps. However, these techniques are not equally effective in each particular case. For this reason, engineers distinguish semantic, instance, and panoptic segmentation:
- Semantic segmentation matches every pixel with a corresponding class, such as people, flowers, buildings, etc. With this technique, objects of the same class are labeled as a single entity;
- Instance segmentation is more detailed and identifies objects separately from one another, regardless if they are from one or different classes;
- Panoptic segmentation combines the capabilities of the two and gives each pixel a semantic label and an instance ID.
These are the most common computer vision tasks based on image segmentation techniques:
- Object classification. CV algorithms analyze visuals and attribute them to a certain category. For example, flowers on a lawn or cats on a couch.
- Object detection. After analysis, the system finds a particular object among other objects. For example, a specific flower or cat.
- Object tracking. Algorithms process a video, identify a particular object, and track its movement.
How does computer vision work?
It is widely believed that the human brain can recognize images thanks to numerous patterns. Computer vision follows the same principle. It recognizes patterns to decode visuals in front of them.
In a more technical language, computer vision systems see each picture as a set of pixels, which, in turn, have their color codes. Here is an example from the article written by Golan Levin.
What we see on the left is a set of pixels that together depict Abraham Lincoln. In the middle image, there are different codes for pixel colors from 0 to 255. The right image also depicts Abraham Lincoln but as a set of numbers. This is what a machine eventually “sees”.
All recent advancements in the computer vision niche became possible thanks to deep learning and neural networks. Here are a few words about them as well.
Applications of Computer Vision in 2023: How Your Business May Change
What stands behind the rapid growth of the computer vision niche? Its high adaptability. CV has found its application in retail, healthcare, transportation, manufacturing, and many other industries. Read on to learn how these industries will continue changing in 2023.
Computer vision in retail
Artificial intelligence applications in retail are limitless, covering, among other things, computer vision algorithms. These are the top use cases for next year:
- Customer tracking,
- Theft detection,
- Social distancing.
Computer vision in manufacturing
CV provides, among other things, the most meticulous quality monitoring and, therefore, improves client satisfaction. But it is not all:
- Visual inspection,
- Quality management,
- Workplace analytics.
Computer vision in transportation
CV solutions offer a variety of opportunities to transportation businesses. The changes may become noticeable in different corners of the world due to roadway safety problems and traffic issues that need to be solved in a short term. What exactly can computer vision techniques provide?
- Vehicle counting,
- Road condition assessment,
- Monitoring driving patterns,
- Pedestrian and traffic sign detection,
- Parking occupancy analytics,
- Automated License Plate Recognition (ALPR).
Computer vision in healthcare
Numerous uses of computer vision provide doctors and patients with previously unknown opportunities in medical service. These may refer either to such trivial things as mask-wearing or serious diagnosis use cases, such as cancer detection.
- Mask detection,
- Diagnosis assistance,
- Cancer and tumor detection.
Computer vision in agriculture
The agriculture industry has to deal with a wide range of uncontrolled business risks related to climate and weather conditions. But what companies can control is their day-to-day operations, and computer vision turns out to be an outstanding assistant for that. Let us look at the CV applications in agriculture that are likely to shape 2023.
- Animal and crop monitoring,
- Farm automation,
- Irrigation management,
- Insect and plant disease detection.
Computer vision in sports
Being human-centered, sports is probably the least expected industry in this article. But it does not mean there is no room for tech innovations. These computer vision business applications may strongly impact the industry in the near term.
- Player pose and movement tracking,
- Ball tracking (goal-line technology),
- Video-based coaching.
In our original blog post, we review each of these applications in more detail and share its benefits compared to other innovations. Follow the link to continue reading.