Thanks to the advancement of artificial intelligence and machine learning, computers are becoming more human-like, and words associated with human abilities are now applicable to computer systems that companies such as NCS provide.
Computer vision is one of them. When you hear the word computer vision, you may imagine a computer being able to see as humans do. And while that is not quite so, computer vision refers to a computer’s ability to interpret and understand digital images or videos.
The Definition of Computer Vision
Computer vision (CV) is a branch of artificial intelligence that teaches computers how to make sense of digital images and videos. It involves processing digital images from cameras, videos, or sensors and recognizing objects, activities, and environments to gain understanding. Using this knowledge, computer vision systems can make decisions like humans.
How does Computer Vision work?
Computer vision systems use machine learning algorithms to analyze digital images and videos. This process involves three steps: pre-processing, feature extraction, and classification. Pre-processing is the first step, where noise in the data is filtered out. Feature extraction follows where areas of interest are identified. Classification is the final stage which utilizes a trained model for analysis.
The Importance of Computer Vision
Computer vision is becoming increasingly important across various sectors of society. Each industry can input data and train the computer to interpret visuals accurately according to their needs. This provides more accuracy and efficiency than manual labor.
This is why it is being adopted in various areas, such as security systems for detecting intruders, facial recognition software for customer service, and medical imaging technology for diagnosing diseases. Computer vision also plays a vital role in autonomous vehicles for transportation, robotics for factory automation and agriculture, and retail analytics for sales analysis.
The Applications of Computer Vision
Computer vision has numerous applications in a variety of industries. Here are examples of how different sectors are currently using computer vision:
Defense and Homeland Security
Computer vision systems are used to detect potential threats in surveillance videos. Homeland security uses computer vision to see objects like guns, explosives, and other suspicious items, even if they are concealed. Likewise, a suspect’s height, clothing, and gait can be monitored by closed-circuit cameras scattered over an area.
Medical Imaging Technology
Computer vision is used to analyze and detect abnormalities in medical images—X-rays, MRI, and CT scan, just to name a few. For example, computer vision can measure bone fractures, diagnose tumors or cancerous cells, and detect diseases like COVID-19. Furthermore, it provides precision surgery and assists with rehabilitation activities.
Computer vision systems are utilized in retail stores for sales analysis and customer behavior patterns by tracking shoppers’ movements. It can also be used to estimate a customer’s gender and age group so that businesses can optimize their marketing strategies accordingly. With the information gathered from computer vision systems, retailers can adjust their in-store layouts and stock more appropriate items to meet customer needs better.
Media and Technology
Computer vision is used in media and technology to generate captions, subtitle translations, facial recognition, scene analysis, and automated video editing. It is also used to analyze images and videos for copyright protection and detect inappropriate content like nudity or violence.
Computer vision can be used for educational purposes, such as tracking students’ activities and analyzing their performance. It is also used to monitor staff attendance, identify potential learners in classrooms, and detect any suspicious activity, such as loitering, vandalism, and even cheating during examinations.
Computer vision is used for vehicle safety systems, such as forward collision and lane departure warnings. It can also be helpful for traffic surveillance to monitor congested roads or detect blocked lanes.
Modern cars also utilize computer vision for a 360-degree system view of the surroundings and an automatic parking feature. In the future, autonomous vehicles will use computer vision to navigate roads without human input.
Computer vision systems can be used in agriculture to identify and sort plants, track crop yield and farmland health, monitor livestock, detect pests or diseases, and automate irrigation. With computer vision, farmers can save labor costs and reduce wastage, leading to more efficient crop production.
The Future of Computer Vision
Computer vision is evolving rapidly due to advancements in artificial intelligence, computing power, and data availability. In the future, computer vision systems can support autonomous driving cars for transportation and warehouse automation for inventory management.
These computer vision applications will also likely assist with medical diagnosis by analyzing patient records and discovering abnormalities in real time. Furthermore, it could be used on robots for enhanced precision and accuracy in manufacturing processes. All these possibilities show that computer vision has a bright future ahead of it!
Computer vision is a powerful technology with numerous applications across different domains. It provides accuracy, efficiency, and cost-effectiveness compared to manual labor. Technology will lead to more opportunities in various sectors, such as security systems, medical imaging technology, retail analytics, media and technology, education, transportation, and agriculture.