What is exactly computer vision?
Computer vision is visual and programming technology that combines camera features with programming languages like deep learning algorithms and machine learning algorithms that use python, R, or other programs.
In computer vision the images, videos, and set of data will be captured, the captured images, videos, and data will be processed to meaningful insights and helps in automated tasks to be done.
Computer vision does the job of eyes of human beings, how eyes are capturing the data, processing to these data will be carried out like the brain of human beings, and inferring the results.
Computer vision is one of the branches of Artificial intelligence.
Computer Vision is a field of AI which trains computer programming and facilitates understanding the image or video captured through the camera.
Deep learning and machine learning help the programmers to interact with cameras by the piece of codes and visuals and recognizing the objects and faces from received data.
Scientists enjoy the challenges and when they are tried to create artificial electronic eyes, they are achieved by implementing various machine learning programs with integrating the camera technologies.
And they named this technology Computer Vision also known as CV technology.
By applying CV technology industries can resolve their complex problem with the automation
Computer Vision takes the following steps to provide the required results
- Acquire
- Process
- Analyze
- Perceive
- Extract
- Present
Computer Vision gives the output in the form of below
- Text
- Numbers
- Detecting Colours
- Reproduce
- State of materials
- The mood of the person
Computer Vision Applications
Computer Vision used in many applications and few applications are listed below
- Face recognition
- Object recognition
- Detecting the activities
- Tracking the actions from images or videos
- Modeling of products and process
- Image reproduction
How Computer Vision works?
In computer vision the models are created with the help of programming languages and data set will be used to train the models created in computer vision.
To get a result, tons of data set will be given to the model with the combination image/videos with the results, and based on the input images, videos and earlier results the models will be understanding that infers the result from the targeted images.
Images, videos, events, or state of anything will be fed into the models, and the model gets trained completely by those data to derive the results.
If you want to do a certain activity after recognizing one event or an action, the models need to be trained with events and actions then only this detects the activity or action and next goes to other activities.
Basically, CV uses the following methods to work 1. Acquire, 2. Process, 3. Analyze, 4. Perceive, 5. Extract, 6. Present
The CV models acquire the images, process, and analyze to have an understanding of the images to extract meaningful data or required data and presenting the automation or visualization.
What is computer vision used for?
Computer Vision is used in many applications in healthcare, automobile, retail, Industrial, Banking, and Agriculture.
CV is used in detecting the disease without touching human or animal bodies and able to reveal what diagnosis needs to be done and what medicine needs to propose.
Automatic cars are also known as autonomous cars or connected vehicles can be driven using this technology, the camera fitted into the front of the car will observe the opposite objects and able to reveal the distance between the objects to the car for users.
In retail, computer vision helps in reducing theft by recognizing the person who does shoplifting and indicating the central team of the retail outlet.
The materials can be handled with the help of computer vision in warehouse management. This results in efficient operation in retail and improves productivity.
In the manufacturing industry, the replication of the machinery can be created in digital form with the help of Computer Vision.
The same concept will be used in Digital Twin where the actual status of the machinery and equipment will be replicated, and this helps in analyzing the current process and improves the running capacity of the equipment.
Due to mass manufacturing and to get extraordinary output these technologies will have high-end cameras where this captures the elements within the machinery or equipment.
In banking sectors, the facial recognition functionality detecting and verifying the data with a central server and ensure the safety and security of the banking functionality.
The drone technology can be used with Computer vision to detect land properties, water contamination, and crop quality.
Computer Vision Syndrome
This is not part of Computer vision technology and this is an eye problem or disease or lack which is caused by over usage of computers.
Is computer vision machine learning?
Computer vision is one of the applications in machine learning, there is a lot of application in machine learning.
CV is one of the fields in machine learning where many developments made in machine learning to use this field effectively.
Machine learning saves the relevant data required to interpret based on the image or video captured from the CV cameras.
The various records will be stored on the different combinations with the image captured which is used to recognize or detect from the targeted information.
What are image processing and computer vision?
Image processing in one of the subset activities of the CV which used to modify its pixels by compressing, enlarging, fine-tuning the captured images for better-having quality of images.
This technology will be used in computer vision and additionally CV is responsible for making decisions based on processed input images or videos and does the task automatically.
The image processing will not do any automatic process and any decision-making process. CV is integrated with machine learning, but image processing is not integrating with any language.
What is the difference between computer vision and machine vision?
Machine vision uses cameras to detect or inspect the objects automatically. This technology is used in manufacturing and production to acquire the data and compare the relevant data with accepted data and rejecting the defective one.
Computer Vision may use or may not use machine vision because computer vision works independently, and machine vision can be a part of the CV.
CV uses any sort of software algorithm, any kind of sensors, and other sources. MV uses only cameras and not sensors.
Machine vision comes first in use and then computer vision.
If we consider MV is the body, then CV is the retina, brain, Optic nerves, and central nervous system.
MV uses cameras to detect the objects and CV uses algorithms to process and interpret the images or videos and instructing other components of any system for automatic processes or tasks.
If CV improves in industry, then it results in the machine vision also evolve to the next level.
What are computer vision techniques?
The various techniques will be used in computer vision to get better results according to the way how computers are used for a particular purpose.
The computer vision techniques help the computer to approach in a certain way to resolve or complete the requirement. This uses several techniques in computer vision.
The techniques in computer visions use as follows
- Image Classification
- Localization
- Object Segmentation
- Semantic Segmentation
- Action Recognition
Image Classification
– Classifying the images into the label, in this set of images will be taught to the computer to say or type or show what all images about.
Localization
– CV finds the object where located in the given images or videos.
Object Segmentation
– Finding each object in the image and draw a box touching all edges of the object according to the type of object in the image.
Semantic Segmentation
– In this, the image will be understood by the pixels of the image and CV classify the object based on the understanding of the pixels derived from the image.
Action Recognition
– CV detects the object from videos and able to understand what action this object is doing and that will be communicated to the central system.
What is a computer vision example?
At present, mobile phones are using computer vision in their technology for face detecting so that mobile phone allows the user to access mobile applications.
The mobile camera detects the sex of a human being whether this is male or female and detecting the age of the person while taking the photos.
Autonomous cars use computer vision technology to understand the roads and lanes and help in identifying the objects in Infront of the car.
Microsoft’s inner eyes help the medical departments to analyze the body and find the tumors in the human body and finding the disease in human or animal bodies.
CV is used in another technology called Digital Twin that produces the digital product in visuals using this any person can interact and collect all the information.
Computer Vision Projects
Computer Vision is the subset of AI that learns and educates by the set of data helps in understanding the object and images uses machine learning and deep learning programs.
There are several projects is going on and used in many organizations listed below,
- Face Detection project
- People Counting project
- Image classification projects
- Image segmentation projects
- QR code Scanner
- Autonomous Cars
- Object Tracking project
- Safety and security projects
- Digital replication projects
- Edge detection practice
- Image redrawing project
- Stitching the images
- Making cartoons by understanding the images
- Air Canvas – interacting with fingers and hands in the air to the computer system
- Color detecting projects
- Projects in criminals study
- Hand gesture recognition
- Image reverse search engine
Summary
Computer vision can be used to detect what human eyes doing for their activity, here machines and software can have the understanding by looking at the images or videos utilizing camera and sensors, other tools.
The automation can be tied up with the computer vision so that images or videos once processed the next activity will be automatically triggered.
There are multiple applications in many areas the CV is used.
So there is a lot of innovation is expected in computer vision by the next 5 years and a lot of work will be automated and hard to say these many people need to look at other jobs because robots are able recognizing the activity or object this automate everything more and improve more productivity.
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