What Is Computer Vision – And Why Is It Trending across Industries?

By Parth Cholera, Published on: 30th August 2022

Globally, the pandemic has completely transformed humans and industries regarding how we work, where we work, and what tools we use to be more productive. As a result, many new technology trends have emerged, and the need for Computer Vision Based Applications has also increased.

While Computer Vision Based Applications have been used in the last decade, the actual concept of computer vision was 1st introduced in the 1970s. The original idea was exciting to know and deliver, but the technology to bring it to life was not enough. In recent years, we have witnessed a significant leap in technology that has put computer vision on the priority list of many industries.

The wait was too long!

From the 1970s to 2012, there wasn’t any movement in the development of computer vision technology. It was only in late 2012 – when the 1st significant computer vision breakthrough was made at the University of Toronto, and the technology has kept improving exponentially since that day.

Convolutional neural networks (CNNs), in particular, have become the neural network of choice for many data scientists, requiring much less pre-programming than other image processing algorithms. In the last few years, CNNs have been successfully applied to identify, detect & track objects, faces, and motions. In addition, it is now being used in annotation and labeling, providing vision to robots and self-driving cars.

What is Computer Vision?

Computer vision is a wide range of artificial intelligence (AI) techniques that deal with how computers can automatically gain a high-level understanding of the meaning and context of the activities or actions that humans perform – that too via manual processing and analysis of digital documents, images, and videos. Computer vision features have a wide spectrum of capabilities & have the ability to solve a variety of problems, depending on business goals.

So let’s find out some of the capabilities of computer vision which can contribute to any business niche & boost its productivity & efficiency

How does Computer Vision work?

Computer Vision algorithms rely upon pattern recognition. Thus, specialists train machines with a wide variety of visual data. First, computers guzzle up thousands of related images. Convolutional neural networks then put together visual images using a jigsaw puzzle concept.

In simple words, machines identify image pieces and label objects on them. After that, they proceed with finding patterns in those objects. Thus, this sophisticated technology gets all the parts of the image together. Finally, it assembles them like a puzzle or shares the output.

Computer Vision works on simple math (some logic as mentioned below):-

  • Linear Algebra: Matrices, Vectors, Singular value decomposition (SVD), etc.
  • Numerical Optimization: First-order optimization methods, second-order optimization methods, etc.
  • Probability and Statistics: Random variables, Probability distribution functions, Bayes theorem, etc.

Computer Vision Types and Capabilities

Computer vision features have a wide spectrum of capabilities and Applications, which are listed below –

  1. Text Detection – Extraction / Optical character recognition (OCR)
  2. Facial recognition
  3. Motion detection / Object tracking
  4. Classification & Segmentation (Masking)
  5. Object detection / Identification: Annotation and Labelling – Annotating visual data & labeling them with useful information or identification within the computer vision process is called image Annotation & Labelling, respectively. Here are some of the most common techniques listed below Bounding box, Polygons & Polylines, Key Point and Geo – Annotation, etc.
Above is an Example – How computer vision works and helps in getting desired meaningful output

Applications of Computer Vision:

There are a lot of industries & areas where Computer Vision can be implemented. Some of the interesting areas where it is being used extensively.

  1. Robots in retail and supply chain
  2. Manufacturing industries for defect detection, assembly line, etc.
  3. CCTV-based security systems
  4. Enabling VR/AR (enhanced images and videos)
  5. Human detection
  6. Medical imaging (e.g., MRI reconstruction, automatic pathology, robots-aided surgery, etc.)
  7. Vehicle and traffic incident detection
  8. Fitness and sports – Tracking Systems
  9. Agriculture field monitoring etc.

Why is computer vision required?

Globally, industries report that they are not only concerned about industrial challenges but they are also concerned about designing & implementing computer vision solutions within the organization as they embark on their journey towards automation & digital transformation.

Key challenges in designing & implementing Computer Vision use cases

  • Lack of Adequate Hardware & Software to achieve end goals
  • Poor Data Quality – Lack of training data as the collected data is insufficient & has various challenges
  • Low accuracy and performance of model development
  • High Complexity & Time-consuming – Implementation, hence costly
  • Deflects from business objectives/goals

In a recent survey, 59% of the voters voted to say that they “Wasted Time & Resources on improving accuracy & 53% said poor domain & process knowledge was another major reason for failure

Key industry challenges

Post-Covid, there is a substantial need to offer more reliable and better services to end customers. A lot of companies are embarking on their journeys towards automation. They are facing the challenges of having a high human dependency on processes. There is a lack of data analytics, insights, and real-time monitoring, and a high turnaround time to get work done. This also leads to poo productivity and efficiency challenges.

The global Computer Vision market revenue is expected to grow from $4.5bn in 2018 to close to $34bn by 2025.

Source: Omdia

In a nutshell

With modernization, we are finally caught up to the original ideas of computer vision, which were thought of in the 70s. The computer vision market is targeted to reach $34bn by 2025. As the benefits are so Impressive (i.e., including accuracy), Reducing  Repetitive & Mundane work, and Cost & Time-savings) that many different industries have deployed it. Computer vision still has some major challenges which are required to be overcome before computers can truly understand actions as humans do. Interestingly, big players like Facebook, Tesla, and Microsoft, as well as small start-ups, are finding new ways how computer vision software can make banking, driving, healthcare, supply chain, and Telecom better and better.

Leveraging 20+ years of R&D and offering enterprise-grade custom services to our clients in various domains, including AI/ML, we have designed & developed a specialized computer vision solution that can address all your needs and provide remarkable improvements.

Stay tuned to our upcoming blogs in this series for deep insights on how computer vision techniques have become a “need for the business” and how it plays a vital role in achieving future technologies, e.g., AR/VR/Metaverse.

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