The Total Addressable Market (TAM) for Image Recognition was valued at USD 43.97 billion in 2022. It is projected to reach USD 201.06 billion by 2031, growing at a CAGR of 18.4% during the forecast period (2023–2031).
An image recognition system is a piece of software or hardware designed to recognize specific features of an image, such as an object, a person, a location, or an action. It uses artificial intelligence (AI) and machine vision technology to analyze a matrix of numbers in a digital image. A pattern or relationship is mapped out in subsequent images by the algorithm, increasing the results' reliability. Principal Component Analysis (PCA), Scale-invariant Feature Transform (SIFT), and Speeded up Robust Features are just a few of the most popular algorithms. These methods are also utilized in machine-based visual tasks, such as tagging image content with meta-tags, searching image content, and directing autonomous vehicles, robotic guides, and other such systems.
Growing Popularity of Al-driven Technologies
The evolution of AI and ML is propelling changes in business structures and practices across a variety of sectors. Computing, pattern recognition, and machine vision are just some of the fields that Al is powering. Revenue-generating applications of Al are expected to spread widely across industries, with static image detection, recognition, classification, and tagging among the most promising. Autonomous machine vision vehicles powered by artificial intelligence bolstered the demand for image detection technologies. In addition, demand is expected to be bolstered in the coming years by the proliferation of Al-based qual search engines for object recognition. Several healthcare applications based on Al, such as contemporary radiology interpretation and chronic diagnosis, are contributing to the growth of this industry. The rise in demand directly results from the proliferation of AI-driven software applications.
Law Enforcement at Customs and Border Protection
Despite the widespread interest in and adoption of Al and computer vision technology for image recognition, national and regional regulations stifle market expansion. For instance, Portland, Oregon, has restricted the use of facial recognition software by city agencies, such as those dealing with the general public and law enforcement. The use of facial recognition technology has become widespread in recent years, making it an integral part of many systems designed to keep the public safe and monitor activity in public spaces. Unfortunately, this technology has been banned in several areas across the Americas, Europe, and Asia due to residential privacy concerns. As a result, restrictions imposed by the government are reducing the need for photo ID systems.
Widening Applicability of Facial Recognition
There has been a rise in the need for Al-supported security camera networks as smart cities and buildings become more commonplace. Many businesses and government agencies use facial recognition software for monitoring purposes. Identification systems based on facial recognition are gaining widespread use in the IT sector for authentication and tracking employee attendance. In addition, airport self-service check-ins and border control check-ins are rapidly adopting face recognition technology. Furthermore, face recognition-based payment solutions are evolving in retail and e-commerce, gaining traction in the BFSI industry. Digital advertising, healthcare, social media, voting, and law enforcement can all benefit from face recognition tools.
The global image recognition market is segmented by component and vertical.
Based on components, the global image recognition market is bifurcated into hardware, software, and service.
The service segment is the highest contributor to the market and is expected to grow during the forecast period. Manufacturers are likely to adopt Automated Image Recognition due to a lack of skilled laborers and the widespread use of automation in the industry. In light of the worldwide spread of the coronavirus pandemic, factories will likely opt for as little human involvement as possible and incorporate as much automation into their production process. The proliferation of mobile devices and other electronic gadgets contributes to the market's expansion. Cloud-based application programming interface (API) tool Microsoft Computer Vision API gives programmers access to image processing and content visualization. The mage recognition program is used by several businesses and organizations to speed up the extraction of text and make it easier to find new content.
Based on vertical, the global image recognition market is bifurcated into BFSI, IT and telecom, retail and e-commerce, manufacturing, government, and others.
The retail and e-commerce segment is the highest contributor to the market and is expected to grow during the forecast period. Online shoppers can use image identification to search for clothing or accessories by photographing a garment, texture, print, or color. The image captured by the smartphone is then sent to an app, which uses AI to scour a database of products for matches. It is possible to use image recognition to check for empty shelves, analyze the competition, and audit product placement. Payments and other transactions can also be authenticated using facial recognition.
The global image recognition market is bifurcated into four regions, namely North America, Europe, Asia-Pacific, and LAMEA.
North America is the most significant shareholder in the global image recognition market and is expected to grow during the forecast period. In terms of embracing cutting-edge innovations and incorporating digital tweaks into tried-and-true procedures, North America has always been a pioneer. There have been more than ten billion sales of smartphones with built-in image recognition technology in North America alone. An image recognition app for Android has also been released by a developer. The image recognition app on your phone makes online shopping a breeze when used in conjunction with these methods. Moreover, it provides protections for autonomous vehicles. As the market for image recognition solutions becomes increasingly competitive, suppliers are feeling pressure to respond by releasing increasingly cutting-edge offerings.
Asia-Pacific is expected to grow during the forecast period. There has been a widespread acceptance of the worldwide trend toward technological integration, abandoning the more old-fashioned methods of the past. Several nations are making plans to build robust digital infrastructure in their homeland. Sales of more sophisticated cameras or mobile phones with powerful integrated cameras that can provide robust image recognition solutions have increased as the GDP of developing countries has grown. The image recognition market is forecast to expand at a staggering rate in Asia and the Pacific. The widespread use of mobile and cloud-based solutions to improve data security is mainly responsible for this expansion. Market expansion is driven by factors such as the rising middle classes in emerging markets like China and India, the proliferation of mobile devices, and the maturing nature of online retail.
Growth in the European market is anticipated over the forecast period due to progress made in automobile obstacle-detection technology. Due to advantages such as gleaning business insights from publicly shared images and automatically sorting untagged photo collections, the image recognition market is predicted to expand rapidly in the coming years. And it provides safeguards for autonomous vehicles. The fiercely competitive market for image recognition solutions has pushed manufacturers to innovate to stay afloat. Growth in the European market for image recognition is anticipated to be steady, driven by the expanding adoption of this technology by UK government agencies. Facial recognition systems are used to confirm or identify individuals. Multiple law enforcement agencies in England and Wales have used live facial recognition in conjunction with the private sector.
The global image recognition market’s major key players are
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