applications of computer vision, use case of computer vision, industrial application of computer vision
REAL-WORLD APPLICATIONS OF COMPUTER VISION IN DIFFERENT INDUSTRIES 2021
Famous applications of computer vision ranging from various industries. There are lots of developers and computer vision scientists who are creating innovation through computer vision.
1.
Transportation
2.
Automotive Industry
3.
Healthcare
4.
Retail Industry
5.
Manufacturing Industry
6. Agriculture
TRANSPORTATION
Vehicle Classification
The Object detection algorithm is proposed to detect vehicle and
tracking vehicle motion using sensors in any indoor. And controlled outdoor
environment solving the important problems for visual surveillance. This
method involves locating a varying number of vehicles and the ability to
classify them to distinguish between vehicles.
Traffic analysis
To know how many vehicles in the current road. Like if there is a
lot of traffic jams occurring or the person going the wrong side in
the way or analyze the traffic. And detect who is going the wrong side of the
people are crossing the line or breaking the traffic rule or to overcoming
traffic in the area. So we can manage it and counting the vehicles like how
much of the traffic is there. Traffic surveillance provides accurate
vehicle detection. The self-driving car needs to detect the vehicles or from the crossroads like humans or animals are
crossing the roads. So it also did needs to analyze the traffic from
which the vehicle is coming or any person or the animal is
crossing roads or not. Traffic analysis is being used in self-driving cars
to make the car efficient in the self-driving and to avoid any
accidents.
Automated License Plate Recognition (ALPR)
ALPR is used to identify vehicles by their license plates. It uses Optical
Character Recognition (OCR) on images to read vehicle license plates in the
image.
Some of its main tasks are:
·
Image Capture
·
License plate localization
·
Character segmentation, and
·
Identification
OpenALPR is an open-source library for license plate libraries used in
transportation and surveillance systems.
Pedestrian Detection
Pedestrian Detection algorithms use advanced sensors and near-infrared
imaging devices to detect human movements. Then alert the driver or apply an automatic brake.
Security and Surveillance Augmentation
Computer vision technology based on color image processing and analysis. It relies on computer vision technologies as the security or video
surveillance domain.
AUTOMOTIVE INDUSTRY
Self-driving cars
Computer vision technology can enable self-driving cars to classify and
recognize different objects. The vehicle uses LiDAR sensors to determine
ranges and cameras and uses pulsed laser beams to measure distance. These
technology-installed vehicles, process such data to make decisions
in the real world. Thus computer vision helps self-driving vehicles to
identify risks and avoid accidents.
Google has launched
Waymo. It is a branch of Google that works in commercial self-driving taxi services
to optimize transportation. It is launched in phoenix city in Arizona. Where
they have successfully implemented it. They are planning to move to London
for their next phase. Google has developed and worked in
Arizona City.
Tesla
is also making self-driving cars using computer vision and lots of other
companies also provide self-learning car kits. So we can add them in our car
and embed them in our car that would make our ordinary car also the
self-driving.
HEALTHCARE
Cancer Detection
Cancer detection uses machine learning based on how many defected are cells
are in the human body. The computer vision method takes digital images and
diagnoses data from MRI scans to detect diseases like skin diseases and skin
cancer. Doctors are also automating their tasks to give better and efficient
results to provide better cures to the patients. So it is being used in the
medical field.
COVID- 19 Diagnosis
The detection of COVID 19 is also possible with computer vision and many of
the institutes are researching further. Based on the digital chest x-ray
radiography (CXR) images, they are detecting how much the person infected in
COVID 19. We can detect the diseases in the current period of a pandemic.
Medical Imaging
Techniques used to create images of various parts of the body for clinical analysis and medical treatment with the help of digital health.
The computer or electrical device automatically studies an image, X-ray, CT,
or MRI to get useful information from it. It involves the fields of
computer vision and medical imaging that make use of pattern recognition and
signal processing in real-time.
RETAIL INDUSTRY
Inventory Management
The inventory management system is playing a crucial role in computer
vision. Automated computer vision systems can track the current inventory
level in warehouses and product’s shelf life. It sends an email alert to
inventory management about the stock level. It also reduces human error as
it uses accurate bar-code scanning.
Facial Recognition
Face recognition is a way of identification and recognition technique. It is used
to detect human faces whose photos or videos are saved. Facial
recognition systems in our mobile phones it is nothing but computer vision
technology. This technique detects your face landmarks. We have 68
landmarks in our face that detect the edges of our face, eyes, nose, and
chin. Facial recognition is also a part of computer vision. Interesting use
cases of face recognition are preventing retail crime, unlock phones
smarter, advertising, find missing persons, eight forensic
investigations.
Behavioral Tracking
A behavioral tracking algorithm is designed to recognize a face and
determine human characteristics. Such as gender, age, or range. The most
fitting use-case application of behavioral tracking is tracking customer
movement in-store. These can detect walking patterns, analyze navigational routes,
tracking students' behavior, animals movements, etc.
MANUFACTURING INDUSTRY
Symbol Recognition
Optical character recognition systems (OCR) are developed for the
recognition of printed characters or text within a digital image. One of the
applications is to identify the original engine number and chassis number of
a vehicle which is engraved on machine parts.
Predictive Maintenance
Predictive maintenance techniques are designed to an evaluation of the
state making things easier for maintenance. Predictive maintenance is the
system by which machine learning and IoT devices with sensors and
microcontrollers. These can track incoming data from machinery or individual
components.
AGRICULTURE
Crop Monitoring
Crop monitoring helps farmers to track plant growth, soil conditions, and
light intensity with sensors and the quality of crops during the
developmental stage. These can optimize the field and also prevents product
losses.
Disease Identification
In recent years advanced techniques and methods were developed using computer vision. It is used to detect and classify agricultural and horticultural crops diseases to overcome the issues and risks of manual techniques. Machine learning is becoming an integral part of accurate yield mapping. Also, yield estimation, disease detection, crop management, and harvesting using multi-temporal remote sensing imagery processing, soil analysis technologies.
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