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What is computer vision?

Computer vision is a field of artificial intelligence (AI). It enables computers to recognise and understand information in digital images and videos. The technology aims to replicate and automate human capabilities, and to act when it identifies defects. Given its range of practical applications, computer vision is an integral technology in many of today’s leading innovations.

How does computer vision work?

Computer vision analyses large volumes of image and video data until it’s able to recognise the images automatically. It does this through machine learning and a convolutional neural network (CNN).

Algorithms enable the technology to learn on its own, without human intervention. Images are broken down into pixels, which are given labels.

The labels are then used to perform convolutions (the combination of two inputs to produce a third). The technology then makes predictions about the image that’s being analysed. As more convolutions are run, the more accurately the machine can recognise images and detect issues.

The benefits of computer vision

Computer vision is widely used in industries that rely heavily on technology and automation. Some of its benefits include:

Increased efficiency and productivity

Computer vision can automate industrial tasks that are typically performed by humans. As such, it can increase productivity in spaces like warehouses and distribution centres. In turn, businesses can improve their product processing times, increasing efficiency, and saving money.

Better decision-making

Due to the analytical nature of computer vision, the technology can present resolutions that humans may otherwise overlook. It can provide businesses with real-time, accurate insights that enhance decision-making. For example, medics may use computer vision when analysing x-rays or MRI images to detect abnormalities.

Enhanced safety

When used in combination with surveillance technology, computer vision can identify threats and prevent accidents. For example, it can be used to detect approaching hazards in autonomous vehicles. It can also analyse road conditions for emergency vehicles, improving response times.

Improved customer experience

Computer vision can transform how users interact with products and services. For example, in customer support, computer vision enables systems to detect visual cues and identify issues with products. Likewise, it can help businesses personalise their marketing strategies and in-store experiences. By analysing the visual data produced by computer vision, brands can better understand customer preferences and behaviours.

David Plas - people talking at their desk

How is computer vision used across industries?

Computer vision has many applications across industries, including:

Agriculture

When used with cameras and sensors, computer vision can monitor the progress of crops. It can also identify issues like pest infestations and diseases early. Likewise, drones that are equipped with computer vision can be used to map out large fields. It can then provide data on growth patterns and soil conditions. This information can be used by farmers to allocate resources like pesticides, reduce waste, and limit the environmental impact of farming practices.

Transport

In public transportation like air and rail, computer vision can support the monitoring and safety of passengers. For example, it can detect unattended luggage, overcrowding, and raise alerts when passengers need assistance. In self-driving cars, computer vision can help develop collision avoidance systems. Using cameras and sensors, it can detect lane markings, road signs, pedestrians, and other vehicles.

Healthcare

In healthcare, computer vision can support diagnostics and patient monitoring. It can aid decision-making in medical imaging, and assist robotic systems during surgery. For example, in 2022, a robot designed by Johns Hopkins University researchers performed laparoscopic surgery without the guiding hand of a human.

Manufacturing

Computer vision can improve quality control in the manufacturing industry by automating production processes. It can detect assembly errors at high speeds, ensuring that only high-quality products are approved. It can also be used to support robots with tasks like sorting, assembling, and packaging. At Equans, we use computer vision for high-speed detection and recognition of defects in manufactured objects.

The role of computer vision in decarbonisation

One of the core ways computer vision supports decarbonisation is through optimised energy use. It allows systems to monitor and respond to activity levels, and subsequently adjust how power is used.

For example, computer vision-based energy management systems in smart buildings can control lighting, heating, and cooling more precisely. In turn, this helps minimise wasteful energy when spaces are unoccupied, or when natural light is sufficient.

In the fight against climate change, computer vision can also be used to monitor environmental changes. It can observe and quantify emissions and pollutants in real-time. This enables faster and more accurate data collection. Likewise, it can support carbon-sequestering ecosystems by identifying and responding to environmental threats early.

Glossary

Computer vision: A field within artificial intelligence that enables computers to interpret and analyse visual information from the world.

Artificial intelligence (AI): The simulation of human-like intelligence in machines, enabling them to perform tasks that typically require human cognition.

Machine learning: A branch of artificial intelligence that enables systems to learn from data and improve their performance over time without explicit programming.

Convolutional neural network (CNN): A specialised type of artificial neural network designed to process and interpret visual data.

Autonomous vehicles: Self-driving machines capable of navigating and operating without human intervention, using sensors, cameras, radar, and artificial intelligence.

Collision avoidance system: A safety technology designed to prevent or mitigate accidents by detecting potential obstacles and taking corrective actions in real-time.

Laparoscopic surgery: A minimally invasive surgical technique performed through small incisions, using specialised instruments and a camera called a laparoscope.