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Seeing The Future: Advancements in Computer Vision

Jeff ParchetaBy: Jeff Parcheta

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Computer vision is a feature of artificial intelligence that enables computers and systems to obtain meaningful information from anything visual. It uses data and analyzes it repeatedly until it can discern distinction and recognize the images. It is used for object identification, facial recognition, classification, recommendation, monitoring, and detection.

While computer vision has many uses, many industries fail to take advantage of its usefulness in everyday workflows. It can reduce the amount of manual intervention so that employees can focus on more important matters.

How does it work?

Computer vision functions with deep learning and a convolutional neural network (CNN). Deep learning is machine learning that uses neural networks. These networks are made of many layers of artificial neurons that work together. Machine learning uses algorithmic models to enable computers to teach themselves in the context of visual data. Algorithms ensure that human intervention is not needed so that it may run independently.

A CNN aids machine learning to break images down into pixels that are given labels to distinguish. It uses the labels to perform convolutions, a math operation on two functions to produce the third function. The neural network runs the convolutions and verifies the accuracy of the predictions in a repeated iteration until the predictions begin to be true. Computer vision also uses recurrent neural networks (RNN) that process images to find links between them. While CNNs are used for single-image analysis, RNNs analyze videos and understand the relationship between images.

How is computer vision different from image processing? While image processing also uses algorithms to evaluate images, image processing alters them by sharpening, smoothing, filtering, or enhancing. Computer vision doesn't change the image but rather analyzes, understands, and classifies them through labeling. Image processing can be used to modify an image so computer vision can better evaluate it.

How can it be used?

Some might believe that computer vision is used to understand and classify images; however, this technology is also utilized to streamline business operations in many sectors.

Image Classification

Image classification allows computers to see and accurately categorize an image into the appropriate group—computer vision groups similar objects together.

Object Detection

This computer vision ability detects and localizes images. It uses classification to identify, sort, and organize images. This feature is used within industrial and manufacturing processes to monitor and control autonomous applications and production lines. Home camera manufacturers rely on object detection to process live video streams from cameras to identify people or objects in real time and assess if further action is required.

Object Tracking

This feature uses deep learning models to track and identify items according to their groupings. Object tracking can be used in traffic monitoring in human environments. Self-driving cars are constantly taking in all the information around them. While they use computer vision for object detection, object tracking is needed to avoid collisions and obey traffic laws.


This algorithm identifies an object by dividing images of it into different regions based on the pixels seen. It simplifies an image by placing a shape or an outline of the item to determine what it is. Segmentation recognizes if there is more than one object in an image.

Content-Based Image Retrieval

This application within computer vision searches for specific digital images in large databases based on the images' content rather than the associated metadata. It integrates automatic image annotation that replaces manual image tagging. These features can be used for digital management systems and increase search and retrieval accuracy.

Industry Applications

Computer vision has many uses across entertainment, business, healthcare, and transportation. While a relatively straightforward function, it can provide useful insights.

Business Intelligence

Computer vision can analyze images and extract metadata for business intelligence, creating opportunities. It can automatically identify any quality defects before a product is shipped out. It can detect and provide alerts for maintenance and safety issues. It can analyze social media images to evaluate trends and patterns in customer behavior. Additionally, it can authenticate employees with automatic facial recognition.


Healthcare is a big industry whose main focus should be caring for patients. It is the leading industry applying computer vision technology. Medical image analysis visualizes organs and tissues to help medical professionals diagnose quickly and accurately. It can perform tumor detection by analyzing moles and skin lesions. Additionally, its automatic X-ray analysis and symptom discovery from MRI scans prove helpful to health professionals.

Energy & Utilities

Computer vision in the energy and utilities industry has improved safety and helps prevent accidents. A computer vision analysis of electric poles can determine which poles have defects that may spark and turn into hazardous fires. Also, real-time coverage allows deep learning algorithms to spot safety violations in work zones.


The use of computer vision within retail has been exploding with potential. Retailers can create heatmaps using computer vision to track footfall, providing insights into customer behavior. They can adjust merchandising layouts according to these insights. Computer vision can also be effective in inventory management as it determines the number of items in an image or video. It provides workers with real-time updates, enabling them to make informed decisions regarding stock levels.


Computer vision enhances the overall functionality of the agricultural sector. Satellite imaging and UAV footage aid in analyzing tracts of land and improve farming practices. This technology can automate the monitoring of field conditions, the identification of crop disease, the checking of soil moisture, and the prediction of weather and crop yields.

The Game-Changing Power of Computer Vision

In the constantly changing landscape of Artificial Intelligence, computer vision has distinguished itself as a transformative technology that empowers computers and systems to decipher meaningful insights from digital images and videos. Its applications span many industries, revolutionizing processes and opening doors to new possibilities. To bring these revolutionary solutions to your business, contact us today to work with our AI experts to implement cutting-edge technology to take your organization to new heights.


Chetu does not affect the opinion of this article. Any mention of a specific software, company or individual does not constitute an endorsement from either party unless otherwise specified. This blog should not be construed as legal advice.

Founded in 2000, Chetu is a global provider of offshore software development services, solutions and support services. Chetu's specialized technology and industry experts serve startups, SMBs, and Fortune 500 companies with an unparalleled software delivery model suited to the needs of the client. Chetu's one-stop-shop model spans the entire software technology spectrum. Headquartered in Plantation, Florida, Chetu has fourteen locations throughout the U.S. and abroad.

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