Computer Vision : Its Introduction,  Challenges, Benefits, and Applications 

Introduction 

Computer vision and Human vision systems both process visual data in the same way. Computer Vision is an interdisciplinary field related to artificial intelligence, along with machine learning, and a field like an image processing is its subset. It helps the computer to study and identify the 2D type image and map it with a 3D world in the form of a sequence of pictures and videos. Various types of computer vision contain (object, image, edge, pattern) detection, facial recognition, image segmentation and classification, and matching of features. 

The computers are being trained on the huge amount of visual information, that examines and detects all images, the computer processes the pictures and labels objects on them, and also finds patterns in them as well. About, approximately, 3 billion images are being shared, for getting a large amount of data. Computer vision is mostly used in e-commerce and travel websites, social media, and many more. 

Challenges and Benefits of Computer Vision 

• Challenges of Computer Vision : 

1. Building a computer system or machine-based system on human vision functioning is technically a tedious task. 
2. To know the complete functioning of the eye, one must know how its receptors work and brain functions based on its visualizations. 
3. Computer vision technology is executed mostly using both software and hardware together. For the system to be well-efficient sensors, a high-resolution camera is needed. Although the hardware is more expensive, if the hardware is not installed appropriately or if some ambiguity is there, there are chances of losses in terms of the blind spot and system ineffectiveness of computer vision.  
4. Managing poor-quality data and lack of training on the dataset, the collection of large amounts of high-quality relevant data is the basis of making a fully good system. 
5. Some of the challenges faced in computer vision technology are lack of time and the development of models due to inadequate planning. 

• Benefits of Computer Vision: 

Although computer vision has many challenges, it has many advantages and benefits. Without human assistance, many tasks can be performed using computer vision. It provides beneficial end results to firms, some of its benefits are as follows: 

1. Computer Vision technology-based systems simplify our work by carrying out repetitive tasks in a quicker and simpler way. 
2. Better services and products can be provided using computer vision, with no mistakes, and delivering good quality products. 
3. Computer vision won't leave any products and services functions faulty, that's why companies don't need to spend money on this process, which leads to cost reduction. 

Applications of Computer Vision 

In Agriculture 

Computer vision has applications in agriculture that can mainly be used in tracking, and counting animals automatically by monitoring their health, and safety and noticing if they are not lost somewhere. 

The drones are used for the examination of crops and their health using cameras attached to the drone, seeing the level of water, and focusing on those crops which need more attention. 

Another application could be used in detecting pests and automatically releasing pesticides by getting sprayed. 

Computer vision can be used in agriculture to reduce the manual efforts of farmers to go and keep watch daily in the fields. Most companies use it, computer vision systems can fix and warn about agricultural issues and can inspect photos from satellites, or planes in order to detect conditions to prevent financial losses. 

In Manufacturing Industry 

Manufacturing operations in industries undergo many phases to get the desired product. To make the process faster, and automated, here one can implement its application using the computer vision as follows: 

1. With help of computer vision and IoT devices, one can do predictive maintenance that uses machine learning that monitors the components, gather data, and take the right actions before the breakdown inspection of the machinery and components. 
2. In the automobile industry, 3D vision inspection can be used to scan the parts or components at different angles to get a 3D model of the parts. Fault detection can be made using this type of technique. 
3. Other types of manufacturing applications using computer vision include tracking, labeling, and outlining the products to avoid mismanagement. 
4. Computer vision can also be used to automate the method of packing inspection. 

In Augmented Reality 

By using augmented reality, virtual objects can be seen and placed in real surrounding with the help of computer vision. For the same purpose wearables, and smartphones are used for overlaying digital objects in a real-world domain. Computer vision uses augmented reality to give quick assessments, statistics, and facts, related to the concerned products. 

There are augmented reality apps that can help in detecting material things in the real world that are both on surfaces or single objects inside a material area and uses that information to detect the position in the real place, for example, it can be a tabletop, ceiling fan, sofa, etc. 

In Healthcare 

There are many applications in healthcare from tumor detection in the body to mask detection in recent covid times. Computer vision can be used in cancer identification, patient health status, and checkup analysis for diagnosis and prerequisites so that treatment can be given to the patients. 

Further applications of healthcare in computer vision comprise the classification of cells, and the detection of cancerous cells through medical imaging with help of image processing and machine learning. 

Face detection uses masked face recognition to detect the use of masks and other shielding equipment for lessening the spread of the pandemic coronavirus.  

In Security and Surveillance 

Surveillance and Security are other types of applications using computer vision for saving businesses, avoiding thefts and unwanted activities like fraud, and for safety purposes. The applications of computer vision in security and surveillance are as follows : 

1. Prevention from public tragedies in places like shows, sports, or occasions that can have increased chances of having stampedes or terror attacks. 
2. Vehicle surveillance can be done in parking slots using algorithms like image classification. Also, vehicle identification is mostly done by feature detection of vehicles using recognition of number plates in an automated way, it can be identified using OCR known as Optical Character Recognition. 
3. Human detection is done with the help of object detection algorithms and other types of applications are used for understanding the behavior, individual recognition, and movement analysis of people. 
4. Traffic incidents and security are one of the applications of smart cities, and traffic safety detection is used for in-vehicle systems. Both applications can be done using vision-based cameras for detection and identification in traffic-oriented applications.  
5. Safety monitoring of criminal activities and abnormal detection in public places can be done using AI-based video analysis.  
6. Using AI-based vision surveillance system for providing virtual fencing system. 
7. Prevention of fraud and theft in retail by observing customers and ATM theft prevention from unwanted activities can be done by using computer vision, etc. 

Conclusion 

Computer vision is a multiple-field-based domain that can be used in other fields like deep learning, image processing, the Internet of Things (IoT), machine learning, data science, etc. 

It makes the work automated with much lesser complexity. Although its concept was introduced in the early 1950s and experimentation in the 1970s. Its algorithms and applications are still prevailing. 

Many detections and recognition algorithms are related to neural networks, and other types are used for the extraction and classification of images and video for various applications, and products. 

Many companies adopt computer vision irrespective of its merits and demerits, business models can be built and businesses can gain profits effectively with the increase in efficiency.