Northbrook, IL 60062 -- (SBWIRE) -- 08/03/2023 -- The global Image Recognition Market size is estimated at USD 0.2 billion in 2023 and is projected to reach USD 0.5 billion by 2028, at a CAGR of 16.5% from 2023 to 2028, according to research report by MarketsandMarkets™.

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By component, the services segment to register the highest growth rate during the forecast period

Many countries have widely accepted image recognition in this COVID-19 situation. For instance, Moscow, Russia, and China have adopted image recognition, pattern recognition, and facial recognition technologies to detect individuals and resist the spread of virus. As a result of this, the service segment of the image recognition market has witnessed growth.Services for the image recognition market include implementation, deployment, product upgrades, maintenance, and consulting. Increase in the adoption of image recognition software has led to the growth of such services, which help the companies to increase overall revenue and enhance performance. Vendors in the image recognition market sometimes provide services via channel partners; these partners can help strengthen the geographical reach of solution vendors and improve the cost-effectiveness of their software. The growing demand for rich media is expected to drive companies, such as LTU Technologies, and Catchoom, to offer integrated training services, professional services, and support and maintenance services.

Based on vertical, the BFSI segment estimated to hold the largest market size during the forecast period

As the current COVID-19 pandemic is impacting the world and dramatically altering society, governments and corporations are turning to novel uses of biometric technologies to limit contagion and maintain economic opportunities. COVID-19 has accelerated the adoption of AI in healthcare. AI-based tools and solutions can work quickly, be deployed at scale, and respond to the dynamic nature of the crisis. The BFSI vertical adopts innovative technologies due to increased centralization and computerization. The vertical, which includes commercial banks, non-banking financial organizations, and insurance companies, uses image recognition technology for electronic data and content management. The superior image processing technology is used for the automation and digitization of products and services, which ensure the smooth and effective electronic payment of checks, bills, and invoices, thus enhancing the use of mobile/internet banking. The technology also enables safe and secured online transactions.

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North America to hold the largest market share during the forecast period.

Due to the COVID-19 impact, North America is going through tremendous strain, due to which major countries such as the US and Canada are bearing huge losses. The privacy of customers is mostly being affected during this unprecedented time. The rise in the integration of AI with image recognition and AR is expected to drive the market growth in the US and Canada. The US and Canada both have strong economic conditions and are expected to be major contributors to the MFA markets growth. The geographical presence, significant Research and Development (R & D) activities, partnerships, and acquisitions and mergers are the major factors for deploying MFA and services.

Market Players

Key and innovative vendors in the MFA market include Micro Focus (UK), Broadcom (US), Microsoft (US), IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore), Catchoom (Spain), Slyce (US), LTU Tech (France), Imagga (Bulgaria), Vispera(Turkey), Blippar(UK), Ricoh innovations (US), Clarifai(US), Deepomatic (France), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (US).

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Key Dynamic Factors For Image Recognition Market:

The image recognition market has been experiencing rapid growth and significant technological advancements. Several key dynamic factors have been influencing this market. Here are some of the key dynamic factors that were influencing the image recognition market:

Convolutional Neural Networks (CNNs), a deep learning technique, have been particularly effective at improving the accuracy and performance of image recognition systems. Advances in Artificial Intelligence (AI) and Deep Learning.

Computer vision is being more widely adopted in a variety of industries thanks to its applications in fields including agriculture, security, retail, and the automotive and healthcare industries.

Image search and tagging applications are becoming more popular. The popularity of picture recognition technology has been sparked by the growing demand for effective image search and tagging capabilities in content management systems, social media platforms, and e-commerce.

Increased usage of Mobile and Smartphones: The widespread usage of smartphones equipped with high-quality cameras has produced a large archive of photographs, increasing the need for image recognition software for a variety of mobile applications.

Image Recognition Integration in Autonomous Vehicles Among other crucial functions, the development and use of autonomous cars primarily rely on image recognition technologies for object detection, road sign recognition, and pedestrian detection.

Increase in the use of visual content analysis in marketing and social media: Businesses can use image recognition technology to analyse visual information uploaded on social media platforms and gain insight into the attitudes, preferences, and involvement of their customers.

Growing Interest in Security and Surveillance: By providing real-time facial identification, object detection, and anomaly detection, image recognition plays a crucial role in improving security and surveillance systems.

Data accessibility and cloud-based image recognition services: With the advent of cloud-based image recognition services, organisations of all sizes may now more easily access the technology without needing to make significant infrastructure investments.

Regulation and Privacy Issues: As image recognition technology becomes more widely used, privacy and ethical issues as well as worries about possible abuse of the technology have come to light, calling for more scrutiny and laws.

Integration with Internet of Things (IoT) Devices: Image recognition technology is being incorporated into IoT devices, enabling them to understand visual data and make intelligent decisions, driving improvements in smart homes and industrial applications.

Research and development activities are ongoing, and this has led to improvements in picture recognition algorithms and approaches from both academic institutions and technological corporations.

Competitive and Segmentation Analysis:

The image recognition market is fiercely competitive and often changing, with many competitors providing a variety of solutions to appeal to diverse market groups. Based on technology type, application, deployment style, and component, the market can be divided into segments. Traditional image recognition, object detection, facial recognition, pattern recognition, and barcode/QR code recognition are examples of technology kinds. Industries like healthcare, automotive, retail, security, media, entertainment, agriculture, and more use image recognition in a variety of ways. On-premises and cloud-based deployment options are available, and the components comprise software (solutions for image recognition) and services (professional and managed services).

Technology giants like Google, Microsoft, IBM, and Amazon Web Services have made major strides in image recognition technology in this cutthroat market while also providing cloud-based solutions and services. With tailored image recognition offerings, startups and specialised suppliers like Clarifai, Imagga, Visenze, SenseTime, and Trax Image Recognition have also emerged as major participants. The infrastructure for image recognition systems is provided by platform suppliers like NVIDIA and Xilinx as well as cloud service providers like Amazon Web Services, Google Cloud, and Microsoft Azure.

Image recognition services are provided by integrators and solution providers including Accenture, Deloitte, Fujitsu, and Cogizant as a part of broader service offerings. Additionally, industry-specific vendors have carved out their markets, such as Niantic (for augmented reality gaming applications) and NEC Corporation (for facial recognition in security and surveillance).

The effectiveness and performance of image recognition algorithms, a wide range of application capabilities, integration and compatibility with current systems, data security and privacy measures, customization options, high-quality customer support and service, competitive pricing, and ongoing research and development efforts to improve image recognition capabilities are all competitive factors in this market. It will be crucial for businesses looking to stay competitive and grasp new possibilities in this fast-paced industry to monitor the competitive environment and stay on top of emerging trends as the image recognition market continues to expand and evolve.

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