4 Best Computer Vision Use Cases for Solving Business Challenges

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4 Best Computer Vision Use Cases for Solving Business Challenges

Computer vision is a field of artificial intelligence (AI) that can be found in an increasing number of business use cases. It enables machines to “see” objects and interpret them as humans do. Computer vision services specialize in many types of vision, including detection, identification, and supervision. Here’s a quick rundown of both how the technology works and how businesses are using it to overcome challenges and optimize workflows.


How Computer Vision Works

All computer vision devices and applications utilize AI, which is a simulated form of human intelligence and the basis of all machine learning. Just as a human sees an image and processes an appropriate response, the AI in computer vision detects digital images, analyzes the data, and processes a response in the blink of an eye.

For a computer vision system to work effectively, developers must expose it to thousands of images with definitive traits, such as names, physical features, and labels. Pattern recognition is the name of the game. Once the system acquires a knowledge base of its particular environment, it can automatically take over detection, identification, and supervision responsibilities without human assistance.

Computer vision is gaining a foothold in various industries, and business leaders have many opportunities to use the technology and get ahead of their competitors. Here are four of the most influential applications and real-world examples of how computer vision can solve companies’ challenges.


Computer Vision Use Cases for Solving Business Challenges

1. Object Detection

Object detection is the most well-known and widely used computer vision function. A system utilizes its AI network to identify specific objects in various settings. It eliminates much of the programming and guesswork that previous detection devices relied on, allowing for quick and accurate detections without human supervision or intervention.

Self-driving cars are perhaps the most well-known examples of AI-powered object detection, but that technology has seen mixed results in practice. These other real-world applications have been more successful:

  • Home and public security: Security cameras with computer vision can detect facial features, vehicle models, weapon types, and other details that enable identifying suspects with more success.
  • Sales automation: Automated self-checkout stations detect each product a customer brings to the counter. They can be inaccurate, but they have been instrumental in easing labor shortage issues in many retail spaces and thus continue to gain relevancy.
  • Inventory management: A computer vision system can identify missing or misplaced items on shelves, pinpoint low-stocked goods, perform automated quality control checks and eliminate human error from inventory management to help businesses run more efficiently.
  • Agriculture: Farmers can automate visual inspections of their crops, helping them identify unhealthy or contaminated plants. Some have even utilized computer vision in flyable drones to monitor their fields from above, saving valuable time and labor.

Object detection is just the first step in a computer vision service’s analysis. It also classifies, monitors and verifies objects based on what the AI has learned. This technology will only get more accurate as it continues to gather information.

2. Optical Character Recognition

On a smaller scale, computer vision services use optical character recognition (OCR) to identify letters, numbers, and other symbols from images. The most mainstream example of OCR that you might have already used is Google Lens. This tool enables users to pull fragments of text from digital images and printed documents and even translate foreign languages from photographs.

OCR has also been a valuable tool for several key societal institutions, including education, finance, and government. Universities can scan and extract text from obscure historical documents and make more accurate translations, preserving precious knowledge from the past that otherwise might have been lost.

Banks and credit unions offer OCR services so customers can scan their checks and credit cards without coming into the office. Other machine-readable personal documents — passports, driver’s licenses, green cards — also utilize OCR to help governments with border security and identification. Virtually every scannable item you can imagine can benefit from OCR, so your business is sure to find a relevant use for it.

3. Risk Management

Employee safety should be the top priority for all businesses and industries, but equipment and regulations can only do so much. A computer vision system can help create a safer work environment by tracking worker activity, including how they use heavy machinery and navigate the work site.

Safety-oriented computer vision applications are most common in dangerous settings, such as construction sites and warehouses. Workers use wearable AI devices to monitor their physical conditions, while supervisors use drones and cameras to identify hazards and ensure everyone follows required safety procedures.

The health care industry has found a similar use for computer vision services, providing patients with wearables that automatically monitor specific conditions and send feedback in real-time to their doctors. This trend arose by necessity during COVID-19, as many people were either unable or unwilling to schedule in-person appointments.

Computer vision is also a key part of some in-house hospital equipment. Medical professionals can train AI to identify the early stages of illnesses through X-rays, MRIs, and CT scans.

4. Image and Video Restoration

Modern cellphones, cameras, and editing tools allow people to make drastic changes to images and videos, but none of those devices come close to computer vision’s editing capabilities. Computer vision services restore pictures and videos with extensive damage and decades of deterioration.

AI in computer vision services evaluates the missing or damaged parts in the original image or video, reads a generative model of the same media, and fills in the gaps to recreate the scene. Some take the restoration a step further and build 3D sets of real settings, such as archaeological and environmental professionals. 

Computer vision’s restoration abilities have also proven valuable in the court of law, as forensic specialists can perform more immersive crime scene reconstructions and thus solve many cases.


Computer Vision Has Massive Potential

These applications of computer vision services are just a handful of successful examples. This technology has massive potential to transform many crucial industries, from health care to finance to construction. Developers are still working out some of the kinks, but business leaders should embrace this technology and add it to their operations in any way they can.

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