Image Recognition Market Size, Share & COVID-19 Impact Analysis, By Component (Hardware, Software, Services), By Technology (Code Recognition, Facial Recognition, Object Recognition, Pattern Recognition, Optical Character Recognition), By Application (Scanning and Imaging, Security and Surveillance, Image Search, Augmented Reality, Marketing, and Advertising), By Deployment (On-Premise, Cloud), By End User and Regional Forecast, 2020-2027

The global image recognition market size was USD 23.82 billion in 2019 and is projected to reach USD 86.32 billion by 2027, exhibiting a CAGR of 17.6% during the forecast period.

Image recognition technology applies machine learning (ML) or deep learning algorithms to selected images for extracting features, which are further utilized for achieving valuable insights. The development of AI-driven applications including deep learning, neural networks, computer vision, and machine vision has significantly augmented the demand for image identification tools. One of the popular application areas is autonomous or driverless vehicles, where image acknowledgment technology plays a crucial role.  

In various industries, this technology is used for validating different data. The key players operating in the e-commerce, retail, advertising, healthcare, and automotive industries are rapidly adopting image recognition-based applications. These applications are helping enterprises to improve business processes and productivity. The growing potential of computer vision is attracting substantial investments in image detection technologies. The popular applications of image processing include medical image analysis, face detection, gesture recognition, and driverless car vision.   

 COVID-19 Pandemic to Support Moderate Adoption of Facial Recognition Applications

The novel coronavirus pandemic has transformed the world by accelerating digitization trends. All economic sectors have been forced to deploy advanced technologies to transform their traditional business models. The pandemic has led numerous organizations to deploy advanced recognition technologies such as facial recognition for supporting social distancing during the time of the pandemic. Several banking and financial organizations are developing face recognition-based mobile payment services. For instance, in June 2020, CaixaBank, S.A. started a project to roll-out a facial recognition technology at over 100 ATMs across Spain to offer touchless payment withdrawal services to ATM users. The drastic shift of businesses towards digitization is anticipated to boost the usage of image detection and recognition technology.

Moreover, acceptance of advanced technologies such as machine vision, artificial intelligence, and computer vision are promoting the adoption of image detection and recognition technology. Modern chronic disease diagnostic and radiology methods are utilizing intelligent image detection and analytics technologies, which are witnessing promising expansion across the healthcare industry. In December 2019, for instance, the GE Group launched more than 30 imaging intelligent smart devices and applications to improve the efficiency of radiology departments.

However, falling prices of hardware and unfavorable government policies are hampering market growth. The pandemic had slowed production as well as logistic processes, resulting in reduced demand for advanced technologies. Further, the closure of shops and malls has stymied the implementation of magic mirrors and virtual fitting rooms that have diminished the product demand. The governmental bans on facial recognition for security and surveillance have majorly slowed down image identification technology adoption. Hence, the COVID-19 pandemic is likely to have a negative impact on the growth of this market as a result of contracting demand.

LATEST TRENDS

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Emergence of Neural Networks and Deep Learning Algorithms to Augment Demand

Convolutional neural networks (CNN) and deep learning algorithms have been built to augment the image detection and recognition processes. These algorithms are utilizing various AI-based features to detect, analyze, classify, and recognize image pixels more precisely. The quick and upgraded response of image detection and recognition with CNN has escalated its demand across the healthcare, automotive, e-commerce, and gaming industries. Thus, various technology providers are deploying deep learning and neural network capabilities to enhance their image detection and recognition applications. For example, in November 2019, Panasonic Corporation started offering the application program interface (API) for image recognition technology in the Japanese market. These APIs are using deep learning algorithms for enhancing image detection and recognition. Amazon’s Rekognition APIs are also utilizing deep learning algorithms for enabling quick and sophisticated image classification and visual searches.

DRIVING FACTORS

Growing Popularity of AI-driven Technologies to Boost the Market

The development of artificial intelligence and machine learning is driving industry and business model transformations. AI is driving numerous applications including computer vision, pattern recognition, machine vision, and many more. Static image detection, recognition, classification, and tagging are projected to be some of the top revenue-generating applications of AI across industries. Additionally, AI-driven autonomous machine vision vehicles are also stimulating demand for image detection technologies.

Apart from this, the increasing popularity of AI-based visual search engines for object recognition is anticipated to fuel product demand in the coming years. Several AI-based healthcare applications such as modern radiology interpretation and chronic diagnosis are enhancing the value of this market. Thus, the development of artificial intelligence-based applications is simultaneously escalating the demand for the product.  

Widening Applicability of Facial Recognition to Propel Demand

The development of smart cities and buildings is stoking the demand for AI-supported security camera networks for robust surveillance. Many public as well as private sector entities are adopting face recognition technology for surveillance purposes. The IT industry is majorly adopting face recognition-based identification systems for authentication and staff attendance purposes. Besides this, face recognition technology is becoming essential for self-service check-ups and border check-ups at airports.

Furthermore, the retail and e-commerce industries are evolving face recognition-based payment solutions, which are also gaining traction across the BFSI industry. In October 2019, for instance, Google LLC updated its Google Pay Android mobile application to support facial recognition along with fingerprint recognition technology. Additionally, face recognition tools are also applicable in the fields of digital marketing, healthcare, social networks, voting, and criminal investigations. The expanding application areas of facial recognition technology are, therefore, fueling the growth of this market.

RESTRAINING FACTORS

 Law Enforcement at Customs and Border Protection to Limit Adoption

In spite of image recognition gaining traction across the public and private sectors, with the growing acceptance of AI and computer vision technology, federal and local regulations are hampering the market growth. For example, in September 2020, Portland, Oregon banned the use of facial recognition technology by various city departments including public-facing businesses and local police. Face recognition technology has to become a common tool in the past several years for ensuring public safety and surveillance. However, this technology has been banned in several regions across the United States, Europe, and Asia-Pacific owing to residential privacy concerns. Such government policies are, as a result, hampering the demand for image identification solutions.

SEGMENTATION

By Component Analysis

Software Segment to be the Dominating Segment

Based on components, the market is segregated into hardware, software and services. Amongst these, the software segment will hold the largest market share. Industry 4.0 revolution and automation is driving the adoption of image detection and recognition algorithms for software product designs and developments. With the increasing potential of computer vision technology, organizations are investing in image detection technologies to analyze and interpret data from visual sources. Numerous trending applications such as biometric or face detection for security, identifying objects in autonomous cars, or medical image analysis are stimulating the demand for image detection and recognition algorithms. The massive deployment of this technology in the gaming, healthcare, automotive, and e-commerce industries is further raising the global market value.

On the basis of services, the market is further classified into implementation services, consulting and training, and support and maintenance services. Among these, implementation services are likely to hold a large revenue share owing to the demand for the integration of the technology into suitable application platforms or technologies.  

By Technology Analysis

Customer-Facing Function to Drive Adoption of AI in the Retail Industry

Based on technology, the market is segmented into code recognition, facial recognition, object recognition, pattern recognition, and optical character recognition. Among these, the code recognition segment is holding a large market share owing to the wide adoption across all industries for data entry and inventory control applications.

Facial recognition technology is expected to demonstrate significant growth in the forecast period. Significant developments in artificial intelligence and machine vision are jointly boosting the adoption of technology in numerous applications. For instance, Brazil has implemented artificial intelligence (AI) in facial recognition systems on a substantial scale. Globally, increasing investments in autonomous vehicles are expected to drive the demand for facial and pattern recognition technologies.  

By Application Analysis

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Security and Surveillance to Emerge as the Leading Segment

In terms of application analysis, the market has been fragmented into scanning and imaging, security and surveillance, image search, augmented reality, and marketing & advertising. Amongst these, the security and surveillance application segment is expected to dominate over other applications. Growing security and public safety concerns are surging the demand for image identification technologies. Various organizations are massively deploying biometric or facial recognition systems for employee identification for attendance and security purposes. Thus, the security and surveillance application is dominating the market in terms of revenue generation.

The other most-favorable segment is augmented reality technology, which is prompting by using this type of recognition technology. The popularity of virtual try-on applications is primarily responsible for this segment’s growth. 

By Deployment Analysis

Adoption of Cloud-based Image Recognition to Fuel the Market

Based on deployment, the market is segregated into on premise and cloud-based. Owing to the massive adoption of cloud applications, the cloud-based segment is likely to exhibit a significant growth rate. Enhanced flexibility, fast deployment, scalability, cost-effectiveness, and improved performance encouraging organizations to prefer cloud deployment mode over on premise.

However, security concerns surrounding cloud based integration are favoring the adoption of on premise deployment of image detection technologies.  

By End User Analysis

Media and Entertainment Segment to Exhibit Significant CAGR

In terms of end-user analysis, the market has been divided into BFSI, media and entertainment, retail and consumer goods, IT and telecommunication, government, healthcare, transportation and logistics, and others. Amongst these, the media and entertainment segment is likely to exhibit significant growth owing to the development of the sector with the adoption of cutting-edge technologies. The emergence of technologies such as machine vision, virtual reality, and augmented reality are substantially contributing to the demand for image recognition solutions.

Similarly, the emergence of deep learning and artificial intelligence in the medical sector has fueled the demand for image detection and recognition technology. Advancements in this technology have developed computerized, precise, accessible, and cost-effective medical diagnostics, which are expected to propel the market growth.

Furthermore, image recognition applications such as barcode recognition, QR code recognition, authentication, identification verification, and others are also driving the adoption of image identification tools and solutions across the retail, banking, and e-commerce industries.   

REGIONAL INSIGHTS

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Geographically, the market has been studied across five major regions, namely North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. They are further categorized into countries.

Presently, North America is dominating the image recognition market share, owing to the presence of a large number of prominent market players. In addition, the early adoption of computer vision technologies is strengthening the region’s leading position in the global market. Adoption of software-driven business process automation using cognitive technologies such as text recognition, natural language processing, and image detection & recognition is also supporting the regional market growth. Additionally, the deployment of autonomous vehicles is driving the adoption of recognition solutions across the region. However, in 2019, in response to the concerns regarding privacy and surveillance, the use of facial recognition technology was banned by the government agencies in San Francisco. The preemptive step by the city’s government is negatively impacting the regional market growth.  

Increasing utilization of image and pattern recognition technologies for identification purposes is driving market growth across Europe. The development of 3D vision autonomous vehicles in the region is also providing strong support to this market. Apart from this, the use of facial recognition technology for public security and surveillance has boosted product adoption in several European countries. However, the adoption of facial recognition technology is likely to decline as the European Commission has banned the use of technology for public surveillance for the next five years.

Asia Pacific is anticipated to demonstrate the highest CAGR during the forecast period owing to the increasing use of cognitive applications across the rapidly developing IT industry in the region. Moreover, AI in healthcare with image detection and recognition technology is streamlining chronic disease diagnosis, which in turn is fueling the regional market. Increasing investments in artificial intelligence and integration of computer vision and facial recognition technologies are strengthening the market position of Asia Pacific.

KEY INDUSTRY PLAYERS

 AWS Offers Superlative Image Detection and Recognition Solutions through Amazon Rekognition Platform

Amazon Web Services Inc. (AWS) established the Amazon Rekognition platform in March 2016, specifically to develop image recognition-related products and solutions. The platform is continuously developing innovative solutions by using advanced technologies such as deep learning and convolutional neural networks. This platform enables the identification of people, objects, scenes, text, and activities in the videos and images to detect any inappropriate content. The company also has introduced highly accurate facial search and facial analysis capabilities that can be used to identify, analyze, and match faces for a wide range of people counting, user verification, and public safety use cases.

• March 2019: Amazon Web services (AWS) Inc. announced the launch of its upgraded face analysis features. The new features can be useful to search and categorize large photo collections. The enhancement has improved the accuracy of emotion detection, attributes, and gender identification capabilities of face analytics.

 Key Players to Follow Organic and Inorganic Growth Strategies to Stay Competitive

The key market players are investing their efforts in the development of innovative image identification technologies. To enhance the accuracy of their systems, cutting-edge technologies such as augmented reality, artificial intelligence, and machine learning algorithms are being used by the key players. Tech giants such as Amazon Web Services (AWS), Microsoft Corporation, Google LLC., and IBM Corporation are investing heavily to advance their image recognition offerings. Enhancements to the product portfolios are helping key players to maintain their competitive edge. These companies are also engaging in strategic partnerships, acquisitions, and collaborations for expanding their businesses and distribution networks to maintain their market lead.

• July 2019: Star Alliance Services GmbH partnered with NEC Corporation to develop a biometric data-based identification system for pass-through areas such as check-in kiosks and boarding gates at the airports.

LIST OF KEY COMPANIES PROFILED:

• Amazon Web Services (AWS) Inc. (Seattle, Washington, United States)


• Google LLC (Mountain View, California, United States)


• IBM Corporation (Armonk, New York, United States)


• Microsoft Corporation (Redmond, Washington, United States)


• Nvidia Corporation (Santa Clara, California, United States)


• Honeywell International Inc. (Charlotte, North Carolina, United States)


• Qualcomm Technologies, Inc. (San Diego, California, United States)


• Hitachi, Ltd. (Chiyoda City, Tokyo, Japan)


• LTU Technologies (Paris, France)


• NEC Corporation (Minato City, Tokyo, Japan)


• Catchoom Technologies, S.L. (Barcelona, Spain)


• Slyce Acquisition Inc. (Philadelphia, PA, United States)


• Wikitude GmbH (Salzburg, Austria)


• Blippar Ltd (London, England)

KEY INDUSTRY DEVELOPMENTS:

• May 2020 – Fujitsu Research and Development Center Co., Ltd. (FRDC) and Fujitsu Laboratories Ltd. have developed a hand wash movement recognition system named Actlyzer. The system leverages artificial intelligence (AI) and machine learning technologies for detecting complex hand washing actions by using video data captured by a camera.


• May 2019 – Wikitude GmbH has introduced a new image target collection and transparent area features to its image recognition engine named Wikitude SDK 8.5. These enhancements will help the company in strengthening its product portfolio.

REPORT COVERAGE

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The image recognition market research report provides a detailed analysis of the market and focuses on key aspects such as leading companies, product types, and leading applications of the product. Besides this, the report offers insights into the market trends and highlights key industry developments. In addition to the aforementioned factors, the report encompasses

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