Computer Vision in Artificial Intelligence. how it works & where its used ?

What is computer vision:   

computer vision is a model of Artificial Intelligence, that enables computers to be able to observe the outer world real-time visible data and make decisions according to the situation demand. In the late 1960s, computer vision started at universities which were exploring artificial intelligence. There are some related fields to Computer Vision like Machine vision, Image processing. Some real-world product use cases of computer vision are defect detection on the assembly line, CT scans brain injury identification, Casino surveillance, self-driven automobile, crop insurance for agriculture, face recognition etc. 

How Computer Vision Works-    

Basically, Computer Vision works with some simple steps such as 

1. Acquiring the visible image 
2. Processing acquired image 
3. Understanding the image to produce information

Image segmentation: - This process makes partitions of an image into multiple sections or pieces to be analyzed individually. Typically it is used to locate objects and boundaries (lines, curves, etc.) 

Object detection: - This process is used to identify a specific object in an image using image recognition. Advanced object detection recognizes many objects also identifies and analyses moving object like people or cars.

Facial recognition: - Face recognition technique is been widely for many reasons mostly for security reason as it can identify a specific individual from an image for verification.

Edge detection: -  This feature gives the advantages of detecting corners and edges of a surface of an object.

Pattern detection: - Pattern recognition is the automated recognition of patterns and regularities in data. It recognizes repeated shapes, colours and other visual indicators in images.

Image classification: - This process classifies images into multiple categories.

Feature matching: - is a type of pattern detection that matches similarities in images to help classify them.

Some simple process like security camera uses one of these processes, but in case of more advanced uses, like computer vision for self-driving cars, rely on multiple techniques to accomplish their goal. Face-mask detection technology using artificial intelligence and deep learning .

Introducing Computer Vision | Face Recognition |Vehicle Automation | Image Analysis

Below is the brief version of all the possible & real-world use cases application of computer vision

Behavioural Tracking :- 

Behavioural tracking algorithm is designed to recognise a face and determine human characteristics such as gender or age range. The most fitting use case applications of behavioural tracking are tracking customer movement in-store, detect walking patterns, analyse navigational route, tracking students behaviour, animals movements etc..

Inventory management :- 

The inventory management system is one of the circumstances where computer vision is playing an important role. Automated computer vision systems can keep an eye on the current inventory level in warehouses and send an email alert to inventory management.

Image Analysis :-  

imaginative and prescient is the art of distilling actionable statistics from pictures. Picture analysis is whilst a laptop or electric tool automatically studies an picture to gain beneficial records from it. It involves the fields of computer or device imaginative and prescient, and scientific imaging, and makes heavy use of pattern popularity, virtual geometry, and signal processing.

Real-time object detection and tracking :-  

Real-time object detection algorithm is proposed for reliably tracking human motion in any indoor & controlled outdoor environment, solving the important problems for visual surveillance. This method involves locating a varying number of objects and the ability to classify them, to distinguish between objects.

Predictive Maintenance :- 

Predictive maintenance technique enables evaluation of the state making things easier for the maintenance personnel. Predictive maintenance is the gadget with the aid of which gadget gaining knowledge of and IoT gadgets display incoming facts from machinery and every now and then person additives through sensors.

Face Recognition :-

Face Recognition is a recognition technique used to detect the faces of individuals whose images saved in the data set. Interesting use cases of face recognition are Prevent Retail Crime, Unlock Phones, Smarter Advertising, Find Missing Persons, Aid Forensic Investigations.

Symbol Recognition -  

Optical character recognition systems (OCR) has been effectively developed for the recognition of printed characters. One such utility is the identifying engine range and chassis number that's engraved on gadget parts.

Security and Surveillance augmentation :-  

Computer vision technology based on colour-image processing and analysis is useful, it relies on computer vision technologies is the security or video surveillance domain. The computer vision system can also be used for indoor surveillance like baby monitoring, patient motoring.

Language Translator -   

The computer vision and machine learning can be applied to recognize specific phonological parameters and epenthesis unique to sign languages and speech recognition. AI language algorithms have resulted in some distance greater specific language translations than have been formerly concept possible.

Autonomous vehicles :- 

The computer vision technology can enable self-driving vehicles to classify and detect different objects. The vehicle can use Lidar sensors and cameras, and the former can use pulsed laser beams to measure distance. Those tech-orientated motors process such statistics instantly to make selections in real-time. Accordingly, pc imaginative and prescient will allow self-using vehicles to identify obstacles and keep away from collisions and accidents.

Disease Identification -   

In recent years, numerous methods were developed using computer vision to detect and classify agricultural and horticultural crops diseases to overcome the problems of manual technique. Also, machine learning is becoming an integral part of accurate yield mapping, yield estimation, disease detection, crop management, and harvesting using multi temporal remote sensing imagery processing, soil analysis technologies. How artificial intelligence is changing the commercial enterprise.

Advantages of Computer Vision

Fast & Simple method - Computer vision has been used in many places it has proved to be faster reliable worthy of replacing manual processes.

Accuracy - Computer Vision-based products have also been daily used and it has never in terms of consistency and accuracy always have been provided accurate faster results using image process flawless process.

Reliability- As programs and bots have proved over time as most reliable than humans as its error-free 

Cost Reduction - With integrating compute vision in business it will save a lot of many as it can take a lot of manual tasks and human effort will be less on the process with faster, reliable & error-free process.

Usability - As of today's modern business with computer vision can be integrated and use in multiple places like the banking sector, medical industry, factories, production companies, Airport & stations etc, which will reduce the effort of physical security & training.