Have you ever thought about how Facebook recognizes most people in the pictures? Or how is Snapchat able to put a dg filter on your faces? These are just a few examples of how computer vision systems are used. 


According to Forbes, the computer vision and pattern recognition market is expected to grow to $49 billion by the end of 2022 while growing at a rate of 7.8% CAGR. It will likely be a source of ongoing innovation and breakthroughs in the coming years. 


But what exactly is Computer Vision?  


A subset of Artificial Intelligence, Computer Vision refers to designing and developing systems capable of capturing information from multidimensional visual data. Briefly, computer vision is the automation of human sight, which is human’s one of the most important senses. The Computer Vision provides the ability to automate it, which opens up great opportunities to develop each sector of the economy. 


CV is a broad technological field that analyzes images or sequences of ideas to extract information. It includes image recognition, video recognition, optical character recognition, and computer algorithms to understand the content of digital images. 


Given the pandemic, many businesses have faced a tragic downfall, and the advancement in the field of Artificial Intelligence and Machine Learning has contributed significantly to the growth of computer vision in recent years. IT has increased so much that it outdoes humans in tasks like objection detection, data analytics, quality control, etc. 



How Computer Vision Trends Help Start-up Founders?


Computer Vision Startup founders and business leaders are often uncertain about the different computer vision applications they should employ in their products or services. Additionally, the related struggles and challenges also pose huge questions. There are various startups where founders have included the CV in their products, which has significantly impacted the creation of valuable products for the customers. 


MDacne is a mobile platform that uses AI and CV to help people with acne. The idea is to put the patients into the center using intelligent algorithms to provide real-time mobile tools to people with health disorders. The application immediately analyses the image using AI, and based on that assessment; the startup founders deliver the fully personalized treatment to the users’ doorstep. 


Hepta Airborne, another CV-based startup, helps the power line utilities to inspect the power grids with the help of drones to capture the data and a specialized inspection platform to analyze it. CV algorithms detect issues in the power grid assets, enabling the operators to fix them and ensuring that the people have a more stable power supply. 


Studying the two use cases above mentioned, one can analyze that a CV can help the startup founders in:



Today various applications, softwares, and product developments across multiple industries are utilizing Computer Vision. From Agriculture to retail, insurance to construction, entrepreneurs apply computer vision to a wide range of industry-specific use cases. 


Top 6 Computer Vision Trends



Did you know in 2020, during the pandemic, Neurala: a company based in Boston, launched its flagship Visual Inspection Automation software, an integrated solution to help the manufacturers ensure the quality inspections on the production lines. 


In various sectors and organizations, quality control is a manual operation. Indeed, the ability of humans to visually inspect different objects is very high, and the subjectivity and the fatigue resulting from repetitive tasks result in human errors. CV-based automated systems offer an adequate quality and process control solution, adding value to the inspections due to enhanced productivity, manufacturing processes’ accuracy, and operational cost reduction. 


Supply Chain issues, labor shortages, and the risk of recalls are driving the need for more automation with each passing day. The manufacturers can scale the production, reduce waste, and adapt to the workforce changes while achieving higher quality controls with the help of the Computer Vision. The computer vision trends go beyond the capabilities of traditional machine vision in detecting anomalies and defects. 


The benefits of this can be defined as follows:


  1. Accuracy: Machines are much more precise than humans, ensuring a higher grade of accuracy within the accepted tolerance in every manufacturing process. 
  2. Repeatability: CV-driven systems conduct monotonous tasks more effectively, and the deployment of the automation results in speeding up the production time. 
  3. Reduced Downtime: The automated system runs much faster and can run 24/7 without any bread. Thus, it reduces downtime. 
  4. Reduced Costs: CV provides tangible economic benefits, and the organizations do not require personnel to perform the quality control of the manufacturer’s products manually. Thus, it reduces the costs. 


CV for Quality Control is increasingly becoming popular within various industries. One of the many industries CV is making its mark in is the pharmaceutical industry. As a result of implementing the CV-based systems, pharma companies are ensuring that each product or tablet meets its relevant quality requirements. 



2. 3D Visual Inspection


AI is a game-changer and is making its way toward production and manufacturing processes to harness the power of deep learning. It involves the analysis of the products for quality control and defects assessments to determine the indicative target features or potential negative impacts.  

computer vision



Any defect or error that may arise due to any injury, fatality, loss of expensive equipment, scrapped items, etc., can result in a significant loss. Various industries require a high level of visual inspection. Fields, where CV-applied 3D inspections have become a must, are nuclear weapons, airport baggage scanning, aircraft maintenance, the food industry, and much more. 



Sticking to manual inspection is not an option for computer vision startups in India, as the old-fashioned way of review requires a presence of a person and an inspector. Typically visual inspection errors range from 20% to 30%, which cannot be eradicated even after hours of training. 


CV-based inspections are better as


3. Safety Assurance


The enterprises need to ensure that their operations don’t compromise safety. Currently, the safety practices are primarily reactive. CV can help these reactive safety measures into proactive ones. Computer Vision is an efficient observer and can help enterprises maintain workplace safety standards. 


With the help of the CV, the organizations can ensure safety in the following areas: 





Computer vision encompasses a diverse array of technologies and applications. By using computer vision, companies can capture and analyze vast amounts of data.  

The CV’s innovative solutions and trends should lead to project scaling and time and money savings. Thus the main recommendations for the startup founders and business leaders are as follows: 

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